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Virtual Instrumenation-Introduction Virtual Instrumentation is the use of customizable software and modular measurement hardware to create user-defined measurement systems, called virtual instruments.




The technology of Virtual Instruments (cont.) • Advantages of Virtual Instruments versus Traditional Instruments Flexibility You can easily add additional functions such as a filter routine or a new data view to a virtual instrument. Storage Today's personal computers have hard disks that can store dozens of gigabytes which is an absolute plus if you want to process mass data like audio or video. Display Computer monitors usually have better color depth and pixel resolution than traditional instruments. Also you can switch easily between different views of the data (graphical, numerical).

What is Virtual Instrumentation? Virtual instrumentation combines mainstream commercial technologies. such as C, with flexible software and a wide variety of measurement and control hardware, so engineers and scientists can create userdefined systems that meet their exact application needs. With virtual instrumentation, engineers and scientists reduce development time, design higher quality products, and lower their design costs.

Why is Virtual Instrumentation necessary? Virtual instrumentation is necessary because it delivers instrumentation with the rapid adaptability required for today’s concept, product, and process design, development, and delivery. Only with virtual instrumentation can engineers and scientists create the user-defined instruments required to keep up with the world’s demands. The only way to meet these demands is to use test and control architectures that are also software centric. Because virtual instrumentation uses highly productive software, modular I/O, and commercial platforms, it is uniquely positioned to keep pace with the required new idea and product development rate

The technology of Virtual Instruments Virtual Instrumentation is the use of customizable software and modular measurement hardware to create user-defined measurement systems, called virtual instruments.




What is a virtual instrument and how is it different from a traditional instrument? Every virtual instrument consists of two parts – software and hardware. A virtual instrument typically has a sticker price comparable to and many times less than a similar traditional instrument for the current measurement task. A traditional instrument provides them with all software and measurement circuitry packaged into a product with a finite list of fixed-functionality using the instrument front panel. A virtual instrument provides all the software and hardware needed to accomplish the measurement or control task. In addition, with a virtual instrument, engineers and scientists can customize the acquisition, analysis, storage, sharing, and presentation functionality using productive, powerful software.

Traditional instruments (left) and software based virtual instruments (right) largely share the same architectural components, but radically different philosophies

One Application -Different Devices For this particular example, an engineer is developing an application using LabVIEW and an M Series DAQ board on a desktop computer PCI bus in his lab to create a DC voltage and temperature measurement application. After completing the system, he needs to deploy the application to a PXI system on the manufacturing floor to perform the test on new product. Alternatively, he may need the application to be portable, and so he selects NI USB DAQ products for the task. In this example, regardless of the choice, he can use virtual instrumentation in a single program in all three cases with no code change needed.

Virtual Instrumentation for Industrial I/O and Control • PCs and PLCs both play an important role in control and industrial applications. PCs bring greater software flexibility and capability, while PLCs deliver outstanding ruggedness and reliability. But as control needs become more complex, there is a recognized need to accelerate the capabilities while retaining the ruggedness and reliabilities. • Multi domain functionality (logic, motion, drives, and process) – the concept supports multiple I/O types. Logic, motion, and other function integration is a requirement for increasingly complex control approaches. • Software tools for designing applications across several machines or process units – the software tools must scale to distributed operation.

Virtual Instrumentation for Design • The same design engineers that use a wide variety of software design tools must use hardware to test prototypes. Commonly, there is no good interface between the design phase and testing/validation phase, which means that the design usually must go through a completion phase and enter a testing/validation phase. Issues discovered in the testing phase require a design-phase reiteration.

On which hardware I/O and platforms does virtual instrumentation software run? • Standard hardware platforms that house the I/O are important to I/O modularity. Laptop and desktop computers provide an excellent platform where virtual instrumentation can make the most of existing standards such as the USB, PCI, Ethernet, and PCMCIA buses.

• for example, USB 2.0 and PCI Express

Layers of Virtual Instrumentation

• Application Software: Most people think immediately of the application software layer. This is the primary development environment for building an application. • Test and Data Management Software: Above the application software layer the test executive and data management software layer. This layer of software incorporates all of the functionality developed by the application layer and provides system-wide data management. • Measurement and Control Services Software: The last layer is often overlooked, yet critical to maintaining software development productivity.

Advantages of Virtual Instruments versus Traditional Instruments Flexibility You can easily add additional functions such as a filter routine or a new data view to a virtual instrument. Storage Today's personal computers have hard disks that can store dozens of gigabytes which is an absolute plus if you want to process mass data like audio or video. Display Computer monitors usually have better color depth and pixel resolution than traditional instruments. Also you can switch easily between different views of the data (graphical, numerical). Costs PC add-in boards for signal acquisition and software mostly cost a fraction of the traditional hardware they emulate.

Dataflow Programming • Block diagram executes dependent on the flow of data; block diagram does NOT execute left to right • Node executes when data is available to ALL input terminals • Nodes supply data to all output terminals when done

Help Options Context Help • Online help • Lock help • Simple/Complex Diagram help • Ctrl + H Online reference • All menus online • Pop up on functions in diagram to access online info directly

Graphical programming in data flow LabVIEW LabVIEW is a graphical programming language that uses icons instead of lines of text to create applications. In contrast to textbased programming languages, where instructions determine program execution, LabVIEW uses dataflow programming, where the flow of data determines execution order. You can purchase several add-on software toolkits for developing specialized applications. All the toolkits integrate seamlessly in LabVIEW. Refer to the National Instruments Web site for more information about these toolkits. LabVIEW also includes several wizards to help you quickly configure your DAQ devices and computer-based instruments and build applications

LabVIEW programs are called virtual instruments (VIs). Controls are inputs and indicators are outputs. Each VI contains three main parts: •Front Panel – How the user interacts with the VI. •Block Diagram – The code that controls the program. •Icon/Connector – Means of connecting a VI to other VIs. In LabVIEW, you build a user interface by using a set of tools and objects. The user interface is known as the front panel. You then add code using graphical representations of functions to control the front panel objects. The block diagram contains this code. In some ways, the block diagram resembles a flowchart

Users interact with the Front Panel when the program is running. Users can control the program, change inputs, and see data updated in real time. Controls are used for inputs such as, adjusting a slide control to set an alarm value, turning a switch on or off, or to stop a program. Indicators are used as outputs. Thermometers, lights, and other indicators display output values from the program. These may include data, program states, and other information. Every front panel control or indicator has a corresponding terminal on the block diagram. When a VI is run, values from controls flow through the block diagram, where they are used in the functions on the diagram, and the results are passed into other functions or indicators through wires.


LabVIEW Programs Are Called Virtual Instruments (VIs)

Front Panel Controls = Inputs Indicators = Outputs Block Diagram Accompanying “program” for front panel Components “wired” together

VI Front PanelPanel Toolbar

Boolean Control

Double Indicator

Waveform Graph

VI Block Diagram

Thermometer Terminal

Call to subVI Knob Terminal

Numeric Constant

Temperature Graph

While Loop

Stop Button Terminal

Stop Loop Terminal

Controls and Functions Palettes Controls Palette (Panel Window)

Functions Palette (Diagram Window)

Graphical, floating palettes Used to place controls & indicators on the front panel, or to build the block diagram

Tools Palette • Floating Palette • Used to operate and modify front panel and block diagram objects. Automatic Selection Tool Operating Tool

Scrolling Tool

Positioning/Resizing Tool

Breakpoint Tool

Labeling Tool

Probe Tool

Wiring Tool

Color Copy Tool

Shortcut Menu Tool

Coloring Tool

Status Toolbar Run Button Continuous Run Button

Additional Buttons on the Diagram Toolbar

Abort Execution

Execution Highlighting Button

Pause/Continue Button

Step Into Button

Text Settings Align Objects Distribute Objects Reorder

Step Over Button Step Out Button

Open and Run a Virtual Instrument Signal Generation and Processing.vi  Help » Find Examples…  Browse According to: Task » Analyzing and Processing Signals » Signal Processing » Signal Generation and Processing.vi

Creating a VI Front Panel Window

Block Diagram Window

Control Terminals

Indicator Terminals

Creating a VI – Block Diagram • After Creating Front Panel Controls and Indicators, Switch to Block Diagram • Move Front Panel Objects to Desired Locations Using the Position/Size/Select Tool • Place Functions On Diagram • Wire Appropriate Terminals Together to Complete the Diagram

Wiring Tips – Block Diagram Wiring “Hot Spot”

Spacebar Flips Wire Orientation

Click To Select Wires

Click While Wiring To Tack Wires Down

SubVirtual Instruments

What is a subVI? • Making an icon and connector for a subVI • Using a VI as a subVI

SubVIs • A SubVI is a VI that can be used within another VI • Advantages – – – –

Modular Easier to debug Don’t have to recreate code Require less memory

Icon and Connector

Icon Terminals


• An icon represents a VI in other block diagrams • A connector shows available terminals for data transfer



Steps to Create a SubVI • • • • •

Create the Icon Create the Connector Assign Terminals Save the VI Insert the VI into a Top Level VI

Create the Icon • Right-click on the icon in the diagram or front panel

Create the Connector Right click on the icon pane (front panel only)

Assign Terminals

Save The VI • Choose an Easy to Remember Location • Organize by Functionality – Save Similar VIs into one directory (e.g. Math Utilities) • Organize by Application – Save all VIs Used for a Specific Application into one directory or library file (e.g. Lab 1 – Frequency Response) • Library Files (.llbs) combine many VI’s into a single file, ideal for transferring entire applications across computers

Insert the SubVI into a Top Level VI Accessing user-made subVIs Functions >> Select a VI Or Drag icon onto target diagram

Tips for Working in LabVIEW • Keystroke Shortcuts – – Activate/Deactivate Context Help Window – – Remove Broken Wires From Block Diagram – – Toggle Between Front Panel and Block Diagram – – Undo (Also in Edit Menu)

• Tab Key – Toggle Through Tools on Toolbar • Tools » Options… – Set Preferences in LabVIEW • VI Properties – Configure VI Appearance, Documentation, etc.

Loops and Charts • • • •

For Loop While Loop Charts Multiplots

Loops • While Loops – Have Iteration Terminal – Always Run Once – Run According to Continue Terminal • For Loops – Have Iteration Terminal – Run According to input N

Loops (cont.) 1. 2.

Select the loop Enclose Code to Repeat

For Loop

Charts Waveform chart – special numeric indicator that can display a history of values Controls >> Graphs >> Waveform Chart

Wiring Data into Charts Single Plot Charts

Multiplot Charts

Monitoring Temperature Students build Temperature Monitor.vi.

Arrays & File I/O • • • •

Build arrays manually Have LabVIEW build arrays automatically Write to a spreadsheet file Read from a spreadsheet file

Adding an Array to the Front Panel From the Controls >> Array and Cluster subpalette, select the Array Shell

Drop it on the screen.

Adding an Array (cont.) • Place data object into shell (e.g. digital control).

Creating an Array with a Loop • Loops accumulate arrays at their boundaries

Creating 2D Arrays

File I/O Easy File I/O VIs

•Read/write to spreadsheet file •Read/write characters to file (ASCII) •Read lines from file •Read/write binary file

Array Functions & Graphs • Basic Array Functions • Use graphs • Create multiplots with graphs

Array Functions – Basics

Array Functions – Build Array

Graphs • Selected from the Graph palette of Controls menu –Waveform Graph – Plot an array of numbers against their indices –XY Graph – Plot one array against another –Digital Waveform Graph – Plot bits from binary data

Strings • A string is a sequence of displayable or nondisplayable characters (ASCII) • Many uses – displaying messages, instrument control, file I/O • String control/indicator is in the Controls»String subpalette

Clusters • Data structure that groups data together • Data may be of different types • Analogous to struct in C • Elements must be either all controls or all indicators • Thought of as wires bundled into a cable

Creating a Cluster 1. Select a Cluster shell from the Array & Cluster subpalette

2. Place objects inside the shell

Cluster Functions • In the Cluster subpalette of the Functions palette • Can also be accessed by right-clicking on the cluster terminal

(Terminal labels reflect data type) Bundle

Bundle By Name

Cluster Functions Unbundle

Unbundle By Name

Unbundled cluster in the diagram

Error Clusters • Error cluster contains the following information: – Boolean to report whether error occurred – Integer to report a specific error code – String to give information about the error

Error Handling Techniques • Error information is passed from one subVI to the next • If an error occurs in one subVI, all subsequent subVIs are not executed in the usual manner • Error Clusters contain all error conditions

error clusters

Case Structures • In the Structures sub palette of Functions palette • Enclose nodes or drag them inside the structure • Stacked like a deck of cards, only one case visible

Error Clusters & Handling

Sequence Structures • In the Structures subpalette of Functions palette • Executes diagrams sequentially, Frame 0 (0..x), where x is the total number of frames • Stacked like a deck of cards, only one frame visible

Sequence Locals

• Pass data from one frame to future frames • Created at the border of the Sequence structure

Data not available

Sequence local created in Frame 1

Data available

• • • • • •

Formula Nodes

In the Structures subpalette Implement complicated equations Variables created at border Variable names are case sensitive Each statement must terminate with a semicolon (;) Context Help Window shows available functions

Note semicolon

Printing & Documentation • • • •

Print From File Menu to Printer, HTML, Rich Text File Programmatically Print Graphs or Front Panel Images Document VIs in VI Properties » Documentation Dialog Add Comments Using Free Labels on Front Panel & Block Diagram

Printing • File » Print… Gives Many Printing Options – Choose to Print Icon, Front Panel, Block Diagram, VI Hierarchy, Included SubVIs, VI History • Print Panel.vi (Functions » Application Control) Programmatically Prints a Front Panel • Generate & Print Reports (Functions » Report Generation) – Search in Find Examples for Report Generation

Documenting VIs • VI Properties » Documentation – Provide a Description and Help Information for a VI • VI Properties » Revision History – Track Changes Between Versions of a VI • Individual Controls » Description and Tip… – Right Click to Provide Description and Tip Strip • Use Labeling Tool to Document Front Panels & Block Diagrams

Simple VI Architecture • Functional VI that produces results when run – No “start” or “stop” options – Suitable for lab tests, calculations • Example: Convert C to F.vi

General VI Architecture • Three Main Steps – Startup – Main Application – Shutdown

State Machine Architecture • Advantages

– Can go from any state from any other – Easy to modify and debug

• Disadvantages

– Can lose events if two occur at the same time States: 0: Startup 1: Idle 2: Event 1 3: Event 2 4:Shutdown

Exercise 7 – Simple State Machine


Introduction to DAQ • Data Acquisition – “Sampling of the real world to generate data that can be analyzed and presented by a computer.”

PC Based Data Acquisition System Overview: In the last few years, industrial PC I/O interface products have become increasingly reliable, ccurate and affordable. PC-based data acquisition and control systems are widely used in industrial and laboratory applications like monitoring, control, data acquisition and automated testing. Selecting and building a DA&C (Data Acquisition and Control) system that actually does what you want it to do requires some knowledge of electrical and computer engineering. • Transducers and actuators • Signal conditioning • Data acquisition and control hardware • Computer systems software

Data acquisition System Introduction I: Data acquisition involves gathering signals from measurement sources and digitizing the signals for storage, analysis, and presentation on a PC. Data acquisition systems come in many different PC technology forms to offer flexibility when choosing your system. You can choose from PCI, PXI, PCI Express, PXI Express, PCMCIA, USB, wireless, and Ethernet data acquisition for test, measurement, and automation applications.

Data acquisition System Introduction II: All industrial processing systems, factories, machinery, test facilities, and vehicles consist of hardware components and computer software whose behavior follow the laws of physics as we understand them. These systems contain thousands of mechanical and electrical phenomena that are continuously changing; they are not steady state. The measurable quantities that represent the characteristics of all systems are called variables. The proper functioning of a particular system depends on certain events in time and the parameters of these variables. Often, we are interested in the location, magnitude, and speed of the variables, and we use instruments to measure them. We assign the variables units of measure such as volts, pounds, and miles per hour, to name a few.

Transducers: Data acquisition systems have multiple components that work together to gather and process information. They can be used to analyze information regarding physical phenomena, such as temperature, voltage, and pressure. However, because temperature, voltage, and pressure are all distinct different, they require different systems of measurement and representation. In data acquisition systems, a transducer serves as the component that translates raw data into a comprehensible electrical signal. When a data acquisition system uses DAQ (data acquisition hardware) the transducer also functions as a sensor, gathering the data from which it will then generate a signal. As a result of all the different variables data acquisition systems can measure, there are several kinds of transducers. A transducer must be capable of generating different signals depending on the particular phenomenon measured. Two general types of signals commonly are used: analog and digital.

Transducer and Acutuator: A transducer converts temperature, pressure, level, length, position, etc. into voltage, current, frequency, pulses or other signals. An actuator is a device that activates process control equipment by using pneumatic, hydraulic or electrical power. For example, a valve actuator opens and closes a valve to control fluid rate.

Signal conditioning : Signal conditioning circuits improve the quality of signals generated by transducers before they are converted into digital signals by the PC's data-acquisition hardware. Examples of signal conditioning are signal scaling, amplification, linearization, cold-junction compensation, filtering, attenuation, excitation, common-mode rejection, and so on.

One of the most common signal conditioning functions is amplification. For maximum resolution the voltage range of the input signals should be approximately equal to the maximum input range of the A/D converter. Amplification expands the range of the transducer signals so that they match the input range of the A/D converter. For example, a x 10 amplifier maps transducer signals which range from 0 to 1 V onto the range 0 to 10 V before they go into the A/D converter.

Signal Conditioning

Electrical signals are conditioned so they can be used by an analog input board. The following features may be available:  Amplification  Isolation Filtering Linearization 

Data acquisition Data acquisition and control hardware generally performs one or more of the following functions: •analog input, •analog output, •digital input, •digital output and •counter/timer functions.

Analog input An analog input converts a voltage level into a digital value that can be stored and processed in a computer. Why would you want to measure voltages? There are a multitude of sensors available which convert things like temperature, pressure, etc. into voltages. The voltages can then be easily measured by various kinds of hardware, such as a LabJack U3-HV, and then read into a computer. The computer can then convert the voltage value into it's original type (temperature, pressure, etc) and the value can then be stored in a file, emailed to someone, or used to control something else outside of the computer.

The most significant criteria when selecting A/D hardware are: 1. Number of input channels 2. Single-ended or differential input signals 3. Sampling rate (in samples per second) 4. Resolution (usually measured in bits of resolution) 5. Input range (specified in full-scale volts) 6. Noise and nonlinearity

Analog to Digital Converter An Analog to Digital Converter (ADC) is a very useful feature that converts an analog voltage on a pin to a digital number. By converting from the analog world to the digital world, we can begin to use electronics to interface to the analog world around us. Not every pin on a microcontroller has the ability to do analog to digital conversions. On the Arduino board, these pins have an ‘A’ in front of their label (A0 through A5) to indicate these pins can read analog voltages. ADCs can vary greatly between microcontroller. The ADC on the Arduino is a 10-bit ADC meaning it has the ability to detect 1,024 (210) discrete analog levels. Some microcontrollers have 8-bit ADCs (28 = 256 discrete levels) and some have 16-bit ADCs (216 = 65,535 discrete levels).

Sampling rate

4 Samples/cycle

Sampling rate is the speed at which the digitizer’s ADC converts the input signal, after the signal has passed through the analog input path, to digital values. Hence, the digitizer samples the signal after any attenuation, gain, and/or filtering has been applied by the analog input path, and converts the resulting waveform to digital representation. The sampling rate of a highspeed digitizer is based on the sample clock that controls when the ADC converts the instantaneous analog voltage to digital values

Analog Input

16 Samples/cycle

8 Samples/cycle

Effective rate of each individual channel is inversely proportional to the number of channels sampled. Example: 100 KHz maximum. 16 channels. 100 KHz/16 = 6.25 KHz per channel.

A/D converter Range Dynamic range is often a key parameter within signal processing systems and a shortfall can limit the quality and range of signals that can be received. The technical progress made on improving this gateway between the analogue and digital world has not kept pace with Moore's law because the challenges are more fundamental than simply reducing transistor sizes. Methods to increase a/d converter dynamic range are therefore always of interest, although each solution often suits particular applications.

Analog output (D/A) An analog output is a measurable electrical signal with a defined range that is generated by a controller and sent to a controlled device, such as a variable speed drive or actuator. Changes in the analog output cause changes in the controlled device that result in changes in the controlled process. Controller output digital to analog circuitry is typically limited to a single range of voltage or current, such that output transducers are required to provide an output signal that is compatible with controlled devices using something other than the controller's standard signal. Common Types:There are four common types of analog outputs; voltage, current, resistance and pneumatic.

Analog output (D/A)

Data Aquisition software

It can be the most critical factor in obtaining reliable, high performance operation. • Transforms the PC and DAQ hardware into a complete DAQ, analysis, and display system. • Different alternatives: – Programmable software. – Data acquisition software packages. •

Programmable software • Involves the use of a programming language, such as: – C++, visual C++ – BASIC, Visual Basic + Add-on tools (such as VisuaLab with VTX) – Fortran – Pascal  Advantage: flexibility  Disadvantages: complexity and steep learning curve

Data acquisition software • Does not require programming. • Enables developers to design the custom instrument best suited to their application. Examples: TestPoint, SnapMaster, LabView, DADISP, DASYLAB, etc. Below is an image with LabView:

Small Computer System Interface [SCSI] Small Computer System Interface (SCSI), an ANSI standard, is a parallel interface standard used by Apple Macintosh computers, PCs, and many UNIX systems for attaching peripheral devices to computers. SCSI interfaces provide for faster data transmission rates than standard serial and parallel ports. In addition, you can attach many devices to a single SCSI port. There are many variations of SCSI: SCSI-1, SCSI-2, SCSI-3 and the recently approved standard Serial Attached SCSI (SAS). SCSI-1 : SCSI-1 is the original SCSI and it is obsolet so far. Basically, SCSI-1 uses an 8-bit bus, and supports data rates of 4 MBps.

SCSI-2 SCSI-2 is an improved version of SCSI-1. SCSI-2 is based on CCS which is a minimum set of 18 basic commands all manufacture's hardware would work together. SCSI-2 also provided extra speed with options called Fast SCSI and a 16-bit version called Wide SCSI. A feature called command queuing gave the SCSI device the ability to execute command in an order that would be most efficient. Fast SCSI delivers a 10 MB/sec transfer rate. When combined with the 16-bit bus, this doubles to 20 MB/sec. This is called Fast-Wide SCSI.

SCSI-3 SCSI-3 has many advances over SCSI-2 such as Serial SCSI. This feature will allow data transfer up to 100MB/sec through a six-conductor coaxial cable. SCSI-3 solves many of the termination and delay problems of older SCSI versions. SCSI-3 eases SCSI installation woes by being more plug-and-play in nature, such as automatic SCSI ID assigning and termination. SCSI-3 also supports 32 devices while SCSI-2 supports only 8.

Data Acquisition System

Analog Signal

Signal Conditioner



Digital Processing

Analog vs. Digital Signal • Analog signals: – Continuous, expressed in decimal system – No limitation on the maximum/minimum value – Can not be processed by computer • Digital signals: binary number system – All numbers are expressed by a combination of 1 & 0 – The maximum value is limited by # of bits available

Signal Conditioning Functions: modify the analog signal to match the performance of the ADC – Pre-filtering: remove undesirable high frequency components – Amplification: amplify the signal to match the dynamic range of the ADC

Analog-to-Digital Conversion (ADC) Function: convert analog signals into digital signals – Sample & hold – Quantization – Coding y(t)=f(t) yk=f(tk)

Quantization Definition: transformation of a continuous analog input into a set of discrete output state – Coding: the assignment of a digital code word or number to each output states – # of possible state: N=2n, n is # of bits – Quantization resolution: Q=(Vmax-Vmin)/N – Quantization Error:    f (t k )  f k N

Select a Data Acquisition Card • Functions: A/D, D/A, Digital I/O, signal conditioning (amplification, prefiltering), timer, trigger, buffer • Features: – A/D resolution (# of bits used) – Maximum sampling rate – # of channels – Total throughput – Aperture time

Example of Data Acquisition Card

What is PXI? • PXI = PCI eXtensions for Instrumentation • Open specification governed by the PXI Systems Alliance (PXISA) and introduced in 1997 • PC-based platform optimized for test, measurement, and control • PCI electrical-bus with the rugged, modular, Eurocard mechanical packaging of CompactPCI • Advanced timing and synchronization features

PXI Systems Alliance (PXISA) • Founded in 1998 • PXISA Goals: – Maintain the PXI specification – Ensure interoperability – Promote the PXI standard • Currently 68+ Members Comprise PXISA • PXISA Website (www.pxisa.org) – Specifications – Tutorials, Application Notes, and White Papers – Locate member companies and products

PXI Specification

Mechanical • High-performance connectors • Eurocard mechanical packaging • Forced-air cooling by chassis • Environmental testing • Electromagnetic testing Electrical • Industry-standard PC buses • System reference clocks • Star trigger buses • PXI trigger bus Software • Microsoft Windows software frameworks • Software components that define HW configuration and capabilities • Virtual Instrument Software Architecture (VISA) implementation

PXI System Overview PXI Controller • Embedded PC, remote PC or remote laptop interface • Runs all standard software


Peripheral Slots

PXI Backplane •PCI/PCI Express bus •Synchronization

Embedded PXI System Controllers Windows-Based Embedded Controllers • High-performance • Integrated peripherals • Entire system in one chassis Real-Time Embedded Controllers • Determinism and reliability with LabVIEW Real-Time • Select high-performance or low-cost/lowpower • Headless operation

Remote PXI System Controllers

PC Control of PXI • Use latest high-performance PCs • PCI Express with MXI-Express • PCI with MXI-4 • High-speed, software transparent links • Up to 110 MB/s sustained throughput • Build multi-chassis PXI systems • Copper and fiber-optic cabling options Laptop Control of PXI • Use latest high-performance laptop computers • ExpressCard with ExpressCard MXI • PCMCIA CardBus • High-speed, software transparent links • Up to 110 MB/s sustained throughput • PXI controllers for portable applications • Use with DC-powered chassis for mobile systems

PXI Chassis Chassis Offering • 4, 6, 8, 14, and 18-slot • Portable, benchtop, and rack-mount • AC and DC options • PXI/SCXI combination chassis with integrated signal conditioning

Wide Range of PXI Modules

Data Acquisition and Control Multifunction I/O Analog Input/Output Digital I/O Counter/Timer FPGA/Reconfigurable I/O Machine Vision Motion Control Signal Conditioning Temperature Strain/Pressure/Force/Loa d Synchro/Resolver LVDT/RVDT Many More. . .

Modular Instrumentation Digital Waveform Generator Digital Waveform Analyzer Digital Multimeter LCR Meter Oscilloscope/Digitizer Source/Signal Generator Switching RF Signal Generator RF Signal Analyzer RF Power Meter Frequency Counter Programmable Power Supply Many More. . .

Bus Interfaces Ethernet, USB, FireWire SATA, ATA/IDE, SCSI GPIB CAN, DeviceNet Serial RS-232, RS-485 VXI/VME Boundary Scan/JTAG MIL-STD-1553, ARINC PCMCIA/CardBus PMC Profibus LIN Many More. . .

Others IRIG-B, GPS Direct-to-Disk Reflective Memory DSP Optical Resistance Simulator Fault Insertion Prototyping/Breadboard Graphics Audio Many More. . .

What’s New in PXI? PXI Express • Increases throughput with 2.0 GB/s per slot dedicated bandwidth • Industry’s best synchronization and latency specification • Ensures compatibility with your existing software and all 1000+ PXI modules

Increased BW Enables New Applications • PXI applications requiring PCI bandwidth – General purpose automated test (DMMs, switching, baseband instruments, etc) – General purpose data acquisition (AI, AO, DIO, etc) – Bus interfaces (CAN, 1553, ARINC, etc) – Motion control

• PXI applications requiring PCI Express bandwidth – – – –

High frequency, resolution IF / RF systems High speed digital interfaces High channel count data acquisition High speed imaging

PXI Express System Timing Slot

PXI Express System Controller

SYNC Control

Differential Star Triggers

PXI Trigger Bus (8 TTL Triggers)

PXI Peripheral

PXI Express Hybrid Peripheral

Star Trigger

PXI Express Hybrid Peripheral

PXI Express Hybrid Peripheral


100 MHz Differential CLK

PXI Express SYNC100

10 MHz CLK

PXI Express System Timing Slot

PXI Express System Controller

SYNC Control

Differential Star Triggers

PXI Trigger Bus (8 TTL Triggers)

PXI Peripheral

PXI Express Hybrid Peripheral

Star Trigger

PXI Express Hybrid Peripheral

PXI Express Hybrid Peripheral


100 MHz Differential CLK

PXI Express SYNC100

10 MHz CLK

Benefits of PXI Express Timing and Synch. Features • Higher performance – 100 MHz differential system reference clock • LVPECL lower jitter clock distribution – Clock 10 < 1 ns skew – Clock 100 < 200 ps skew • Tighter synchronization specifications – Multichassis synchronization with PXIe_SYNC100 – Differential star triggers • Available to all slots • LVPECL low jitter clock, LVDS clocks/triggers for compatibility

PXI and Hybrid Slots Ensure Compatibility

Ethernet-based Industrial Protocols • • • •

Modbus TCP/IP Ethernet/IP EtherCAT Profinet

EtherNet/IP Overview • Dominant bus for Rockwell Automation – Managed by Open Device Vendors Association (ODVA) – Extends DeviceNET concepts to Ethernet

• Advantages – Uses Ethernet transport layer (TCP and UDP)

• Disadvantages – Can overload networks with UDP messages if not correctly configured, recommend managed switches with IGMP snooping

Communication from NI PAC to ControlLogix and ComapctLogix PLCs Ethernet/IP

Uses explicit messaging Available for download from NI Labs

EtherNet/IP VIs for LabVIEW • Provides VIs for communication to “Logix” PLC Tags – Directly read and write tags on Allen Bradley ControlLogix and CompactLogix PLCs • Runs on LabVIEW for Windows and LabVIEW Real-Time (Pharlap and VxWorks) • Explicit Messaging • Good for low numbers of tags

Why Ethernet: Protocols Modbus

Modbus TCP/IP







Traditional Industrial Protocols

Ethernet Physical Layer

Motivations for IVI.NET • Present an API more suited to .NET developers • Simplify source code – Allow end users to understand instrument behavior by examining driver source – Allow end users to fix bugs on their own – Allow end users to add features to drivers on their own • Richer, more expressive APIs – More flexibility with API data types – Clean handling of asynchronous notifications (aka “events”) • Side-by-side deployment of drivers – Only one version of an IVI-COM or IVI-C driver can be installed at a time – IVI.NET allows multiple versions of a driver to be installed

IVI-COM and IVI-C Driver Source • IVI-COM and IVI-C drivers are both quite complicated internally • Supporting IVI driver features requires a lot of code – Multi-thread safety – Simulation – Range-checking – State-caching • “Basic” COM plumbing is complex and not well understood by many • Multi-model driver support can be complicated • Driver development tools are required, but can only do so much – Nimbus Driver Studio and LabWindows both work hard to factor as much code “out of the way”

Advanced Tooling for IVI.NET • Many IVI-COM and IVI-C complaints tied to complex source code • Tools have even more difficulty dealing with C/C++ source than humans – Includes files and macros are particularly problematic – Few really good C++ refactoring exist in any domain • A prime motivator for .NET itself is the improved ability to create tooling • Simpler source possible because .NET code can more easily be roundtripped • Static analysis tools highlight issues at compile time that previously could only be detected at runtime • Browsers can easily interrogate an IVI.NET driver and understand its features • Declarative attributes can be used where procedural code was previously required – Achieved via “extending” the compiler (aka “codeweaving”)

Shared IVI.NET Data Types •

IVI Foundation felt it would be useful to offer commonly used data types as part of the IVI.NET Shared Components – Increase consistency amongst IVI.NET drivers – Facilitate data interchange between drivers Standardized IWaveform and ISpectrum interfaces – Digitizers and scopes and RF spectrum analyzers all read waveforms – Function generators and RF signal generators source waveforms – Without a common definition of a “waveform”, client applications would need to write the tedious code to translate between each class’s notion of a waveform Time-based parameters can use PrecisionDateTime and PrecisionTimeSpan – No confusion about ms vs sec, absolute vs relative time, UTC time, etc – Precision adequate for IEEE 1588 devices Common trigger source data type – Useful in “stitching” together devices in triggered source-measure operations

Error Handling in IVI.NET • IVI-C drivers rely solely on return codes – Errors can easily be ignored by the client application – After getting the error code, a second function call is required to get the message – Special handling of warning codes required • IVI-COM error code handling depends upon the client environment – Return codes in raw C++ – Special exception classes in C++ – COMException class in .NET interop scenarios – .NET clients can’t see warnings at all from IVI-COM drivers • IVI.NET drivers always use exceptions – User can always see the full context of the error – Error content less dependent upon specific driver implementation – Natural mechanism

Performance of IVI.NET • Fewer memory leaks • Reference counting has a cost – Reference count field per-object – Increment and decrement called much more frequently than one might think – Reference count field must be thread-safe • Even more per-object overhead • Frequently lock/unlock operations • Conventional memory-managed systems (such as C-runtime library) produce highly fragmented memory – Allocation of objects can be expensive – Objects spread out in memory => poor locality of reference • .NET memory allocation produces very good locality of reference – Object allocation extremely fast – Objects allocated close together in time live close together in memory – Fewer cache misses and better virtual paging performance

Dynamic Memory Allocation in .NET Start of free space

Managed Heap C1

var c1 = new Car(); var c2 = new Car(); var c3 = new Car();



Free Space



Definition • All Periodic Waves Can be Generated by Combining Sin and Cos Waves of Different Frequencies • Number of Frequencies may not be finite • Fourier Transform Decomposes a Periodic Wave into its Component Frequencies

DFT Definition • Sample consists of n points, wave amplitude at fixed intervals of time: (p0,p1,p2, ..., pn-1) (n is a power of 2) • Result is a set of complex numbers giving frequency amplitudes for sin and cos components • Points are computed by polynomial: P(x)=p0+p1x+p2x2+ ... +pn-1xn-1

DFT Definition, continued • The complete DFT is given by P(1), P(w), P(w2), ... ,P(wn-1) •

w Must be a Primitive nth Root of Unity

wn=1, if 0
Primitive Roots of Unity • wi is an nth root of unity (not primitive) • wn/2 = -1 • if 0£j£n/2-1 then w(n/2)+j = -wj • if n is even and w is a primitive nth root of unity, then w2 is a primitive n/2 root of unity • Example: w = cos(2p/n) + isin(2p/n) n 1

 i 0



Divide and Conquer • Compute an n-point DFT using one or more n/2-point DFTs • Need to find Terms involving w2 in following polynomial • P(w)=p0+p1w+p2w2+p3w3+p4w4+ ... +pn-1wn-1 Here They Are

Windowing and Filtering • Simplest way of designing FIR filters • Method is all discrete-time no continuous-time involved • Start with ideal frequency response 

   h ne

Hd e jw 

1 jw jwn hd n  H e e dw d 2 

 jwn


n  

 

• Choose ideal frequency response as desired response • Most ideal impulse responses are of infinite length • The easiest way to obtain a causal FIR filter from ideal is • More

h n 0  n  M hn   d else  0 generally

hn  hd nwn


1 0  n  M wn   else 0

Windowing in Frequency Domain • Windowed frequency response

 



1 jw j w     H e W e d d  2  

  

• The windowed version is smeared version of desired response

• If w[n]=1 for all n, then W(ejw) is pulse train with 2 period

Properties of Windows • Prefer windows that concentrate around DC in frequency – Less smearing, closer approximation • Prefer window that has minimal span in time – Less coefficient in designed filter, computationally efficient • So we want concentration in time and in frequency – Contradictory requirements • Example: Rectangular window M

  e

W e jw 

n 0

• Demo

 jwn

1  e  jwM 1  jwM / 2 sinwM  1 / 2   e 1  e  jw sinw / 2

Rectangular Window • Narrowest main lob – 4/(M+1) – Sharpest transitions at discontinuities in frequency

• Large side lobs – -13 dB – Large oscillation around discontinuities

• Simplest window possible 1 0  n  M   • wn   0


Bartlett (Triangular) Window Medium main lob

– 8/M • Side lobs – -25 dB • Hamming window performs better • Simple equation

0  n  M/2  2n / M  wn  2  2n / M M / 2  n  M  0 else 

Hamming Window

• Medium main lob – 8/M • Side lobs – -31 dB • Hamming window performs better • Same complexity as Hamming

1   2n   1  cos  0  n  M wn  2   M   0 else 

Blackman Window Large main lob

– 12/M • Very good side lobs – -57 dB • Complex equation   2n   4n  0.42  0.5 cos   0.08 cos  0nM wn    M   M   0 else

Incorporation of Generalized Linear Phase • Windows are designed with linear phase in mind – Symmetric around M/2 wM  n 0  n  M wn   else  0

 

 

W e jw  We e jw e  jwM / 2

 

where We e jw is a real and even

• So their Fourier transform are of the form

 

 

Hd e jw  He e jw e  jwM / 2

• Will keep symmetry properties of the desired impulse response • Assume symmetric desired response 

 

Ae e


1 j j w     H e W e d e 2 

  

• With symmetric window

Linear-Phase Low pass filter Desired frequency response  

Hlp e


e  jwM / 2   0

w  wc wc  w  

• Corresponding impulse response hlp n 

sinwc n  M / 2 n  M / 2

• Desired response is even symmetric, use symmetric window hn 

sinwc n  M / 2 wn n  M / 2

Kaiser Window Filter Design Method • Parameterized equation forming a set of windows – Parameter to change main-lob width and sidelob area trade-off 2   n  M / 2    I0  1      M / 2    wn      I0   0 

0nM else

– I0(.) represents zerothorder modified Bessel function of 1st kind 152

Determining Kaiser Window Parameters • Given filter specifications Kaiser developed empirical equations w  ws  wp – Given the peak approximation error  or in dB as A=20log10  – and transition band width

• The shape parameter  should be 0.1102A  8.7   0. 4   0.5842A  21  0.07886A  21   M


A  50 21  A  50 A  21

A8 2.285w

• The filter order M is determined approximately by

General Frequency Selective Filters • A general multiband impulse response can be written as hmb n 


 Gk

k 1

 Gk 1 

sin wk n  M / 2 n  M / 2

• Window methods can be applied to multiband filters • Example multiband frequency response – Special cases of • Bandpass • Highpass • Bandstop



Digital • Storing information often in a series of 1’s and 0’s or binary numbers. The process can be used to do calculations or sending pulses to regulate instrumentation or other electronic equipment turning it on/off or regulating the use of materials such as the flow of liquid through a valve. In instrumentation and process control this accomplished by concerting an analogue signal into a digital signal to control the process. A non-electronic example would be smoke signals or a beacon.

Analogue • An analog or analogue signal is any continuously variable signal. It differs from a digital signal in that small fluctuations in the signal are meaningful within a given scale range from a small to large signal. Analog is usually thought of in an electrical context, however mechanical, pneumatic, hydraulic, and other systems may also use analog signals. • A great example of an analogue device is a Wrist Watch with hands that move.

Binary • Having the base of 2 for number system with two digits 0 and 1. Basis of electronic signal signals used in computers. Creates two states for the binary signal on or off, 0 being off and 1 being on. There is no state in between the device is either on or off. Often referred to as Boolean Logic

Microprocessor • A silicon based processing chip or logic chip designed as the heart of the computer, contains all the necessary information to run a computer speed measured in megahertz (MHz) or gigahertz (GHz). These chips have areas for comparing numbers or doing calculations called registers. • Good example: Digital Clocks and Wrist Watches

Fuzzy Logic • The ability of a machine to answer questions that are not yes or no questions. Fuzzy logic use 0 and 1 as the extremes of yes and no but answers the degrees of maybe. Fuzzy logic works much closers to that of the human brain. It is subset of Boolean logic use to fill the concepts of a partial truth. An example of such is a half full glass of water is .50 of full.

Neural System • In information technology, a neural network is a system of programs and data structures that approximates the operation of the human brain. A neural network usually involves a large number of processors operating in parallel, each with its own small sphere of knowledge and access to data in its local memory. • Good example: Joystick for a computer game

Sensors • Devices such as a photocell that respond to a signal or stimulus. A device that measures or detects a real-world condition, such as motion, heat or light and converts the condition into an analog or digital representation. These devices are use in manufacturing plants to tell how many items are in a package such as the example CD’s to fill a container for packaging or to the number of containers fill case for shipment. • Good examples: motion detectors and burglar alarms

Actuators • One that activates, especially a device responsible for actuating a mechanical device, such as one connected to a computer by a sensor link. • An actuator is the mechanism by which an agent acts upon an environment. The agent can be either an artificial or any other autonomous being (human, other animal, etc). • Examples: human hand, leg, arm, Part Picking Robot, Switches

Stepper Motors • A mechanism that causes a device to be turned on or off, adjusted or moved. The motor and mechanism that moves the head assembly on a disk drive or an arm of a robot is called an actuator. A good example printer motor moves the laser head cartridge across the paper.

Synchro Motor • A type of rotary transformer fixed to rotor which attached to a motor and can be adjusted. The current is adjusted to keep the rotor and motor operating at a synchronized speed. The result of this action causes the parts to work in unison. • Good Examples: the gun turret on a naval destroyer and the film and sound of older movies before microelectronics.

Open-loop Control • A control loop operated by human intervention or does not have a feedback loop to self adjust. Example A fan that plugs into the wall with no switch to turn on or off.

Plug fan into outlet power on

Fan operates at the speed of the motor

Fan operates to fast to much air movement blows papers of desk

Unplug fan to shut off

Closed-loop Control • A control-loop operated by a feedback loop allowing self adjusting of the loop.” A mechanical, optical, or electronic system that is used to maintain a desired output.” • Good example: Fan with a switch to allow the speed to be changed

Fan plugged in

Fan turned on

Fan is to fast papers blow around

Switch turned down to lower fan speed

Fan works fine papers do not blow around

Fan speed can be adjusted or turned off

Instrumentation • Instrumentation is defined as "the art and science of measurement and control". Instrumentation is used to refer to the field in which Instrument technicians and engineers work. Instrumentation also can refer to the available methods of measurement and control • Good example: the gauges that control the boilers for the school heating system

Development of process database management system

1. Basic Definitions Database: A collection of related data. Data: Known facts that can be recorded and have an implicit meaning. Mini-world: Some part of the real world about which data is stored in a database. For example, consider student names, student grades and transcripts at a university.

Database Management System (DBMS): A software package/ system to facilitate the creation and maintenance of a computerized database. It • defines (data types, structures, constraints) • construct (storing data on some storage medium controlled by DBMS) • manipulate (querying, update, report generation) databases for various applications. Database System: The DBMS software together with the data itself. Sometimes, the applications are also included.

2.File Processing and DBMS File Systems : – Store data over long periods of time – Store large amount of data However : – No guarantee that data is not lost if not backed up – No support to query languages – No efficient access to data items unless the location is known – Application depends on the data definitions (structures) – Change to data definition will affect the application programs – Single view of the data – Separate files for each application – Limited control to multiple accesses - Data viewed as physically stored

3. Main Characteristics of Database Technology

- Self-contained nature of a database system: A DBMS catalog stores the description (structure, type, storage format of each entities) of the database. The description is called meta-data). This allows the DBMS software to work with different databases. - Insulation between programs and data: Called program-data independence. Allows changing data storage structures and operations without having to change the DBMS access programs. - Data Abstraction: A data model is used to hide storage details and present the users with a conceptual view of the database; does not include how data is stored and how the operations are implemented. -

• Support of multiple views of the data: Each user may see a different view of the database, which describes only the data of interest to that user. •

Sharing of Data and Multiple users

DBA – Database Administrator - Responsible for authorizing access to the database, coordinating, monitoring its use, acquiring hardware, software needed. Database designers - Responsible for identifying the data to be stored, storage structure to represent and store data. This is done by a team of professionals in consultation with users, and applications needed.


4. Additional Benefits of Database Technology

Controlling redundancy in data storage and in development and maintenance efforts. Sharing of data among multiple users. Restricting unauthorized access to data. Providing multiple interfaces to different classes of users. Representing complex relationships among data. Enforcing integrity constraints on the database. Providing backup and recovery services. Potential for enforcing standards. Flexibility to change data structures. Reduced application development time. Availability of up-to-date information. Economies of scale.

5 When not to use a DBMS Main inhibitors (costs) of using a DBMS: - High initial investment and possible need for additional hardware. - Overhead for providing generality, security, recovery, integrity, and concurrency control. When a DBMS may be unnecessary: - If the database and applications are simple, well defined, and not expected to change. - If there are stringent real-time requirements that may not be met because of DBMS overhead. - If access to data by multiple users is not required. When no DBMS may suffice: - If the database system is not able to handle the complexity of data because of modeling limitations - If the database users need special operations not supported by the DBMS.

6. Data Models Data Model: A set of concepts to describe the structure (data types, relationships) of a database, and certain constraints that the database should obey. Data Model Operations: Operations for specifying database retrievals and updates by referring to the concepts of the data model.

DBMS Languages Data Definition Language (DDL): Used by the DBA and database designers to specify the conceptual schema of a database. In many DBMSs, the DDL is also used to define internal and external schemas (views). In some DBMSs, separate storage definition language (SDL) and view definition language (VDL) are used to define internal and external schemas. Data Manipulation Language (DML): Used to specify database retrievals and updates. -DML commands (data sublanguage) can be embedded in a general-purpose programming language (host language), such as COBOL, PL/1 or PASCAL. - Alternatively, stand-alone DML commands can be applied directly (query language).

High Level or non-Procedural DML – Describes what data to be retrieved rather than how to retrieve. - Process many records at a time - SQL Low Level or Procedural DML – It needs constructs for both, what to retrieve and what to retrieve - Uses looping etc. like programming languages Only access one record at a time

DBMS Interfaces - Stand-alone query

language interfaces. Programmer interfaces for embedding DML in programming languages: - Pre-compiler Approach - Procedure (Subroutine) Call Approach User-friendly interfaces: - Menu-based - Graphics-based (Point and Click, Drag and Drop etc.) - Forms-based - Natural language - Combinations of the above - Speech as Input (?) and Output - Web Browser as an interface -

Classification of DBMSs Based on the data model used: Traditional: Relational, Network, Hierarchical. Emerging: Object-oriented, Object-relational. Other classifications: Single-user (typically used with micro- computers) vs. multi-user (most DBMSs). Centralized (uses a single computer with one database) vs. distributed (uses multiple computers, multiple databases) Distributed Database Systems have now come to be known as client server based database systems because they do not support a totally distributed environment, but rather a set of database servers supporting a set of clients.

Simulation of systems using VI

SPICE Introduction • SPICE – Simulation Program with Integrated Circuit Emphasis – Developed at University of California at Berkeley – Three revisions, SPICE-3F5 is current • Other circuit simulation technologies – XSPICE – behavioral SPICE – combines SPICE with component behavior in C – VHDL – Programmable Logic Design – IBIS – Used to model transfer function of sophisticated components (A/Ds, etc…) – PSpice®, HSPICETM – commercial variations of the Berkeley SPICE. – RF with Electromagnetic Field Solvers (Agilent Advanced Design SystemTM or Ansoft Designer ®)

SPICE Primer

• SPICE Circuit – Built by creating a netlist of native SPICE primitive models. – Netlist is a text file that lists all connections and model information. – Schematic File • Vendor specific • May include package, footprint, and additional information – SPICE adds analysis commands on top of SPICE file allowing a SPICE simulation to extract information out of circuit (Transient, AC, Monte Carlo etc…) • Variety of native SPICE components: – Resistors, Capacitors, Inductors, Sources, Transistors, etc…

Advantages to Using SPICE with Virtual Instrumentation Mathematical capabilities of SPICE to accurately model complex circuits and devices - AND – Measurement capabilities of Virtual Instrumentation (such as data collection, automation, testing, etc) SPICE

Virtual Prototype

VI Software

Schematic, Simulation, Analysis


Virtual Measurements

Comparison between simulation data and measurements is simplified

Measurements Physical Measurements

Simulation and Measurements for Design Engineers •How do you effectively compare test bench data with simulation data? •How can you bring in measurement data into simulation? •Is there anyway to perform simulations, compare results and optimize the design automatically?


Logic Analyzer

Power Supply

Function Generator


Multisim and LabVIEW Integration

1 .Build Circuit and Simulate in Multisim

2. Use LabVIEW to generate realistic test and/or stimulus waveforms

3. Create Measurements in LabVIEW Reflective of real tests done during testing 4. Once Hardware Prototype is completed, use same measurements for validation testing. 5. Key Step: Compare Measurements and Simulation Data for Improving Design Functionality and Performance

Development of Control system In this chapter we describe a general process for designing a control system. A control system consisting of interconnected components is designed to achieve a desired purpose. To understand the purpose of a control system, it is useful to examine examples of control systems through the course of history. These early systems incorporated many of the same ideas of feedback that are in use today. Modern control engineering practice includes the use of control design strategies for improving manufacturing processes, the efficiency of energy use, advanced automobile control, including rapid transit, among others. We also discuss the notion of a design gap. The gap exists between the complex physical system under investigation and the model used in the control system synthesis.

System – An interconnection of elements and devices for a desired purpose. Control System – An interconnection of components forming a system configuration that will provide a desired response. Process – The device, plant, or system under control. The input and output relationship represents the cause-and-effect relationship of the process.

Control System • Control is the process of causing a system variable to conform to some desired value. • Manual control Automatic control (involving machines only). • A control system is an interconnection of components forming a system configuration that will provide a desired system response. Input Signal

Control System Energy Source

Output Signal

Open-Loop Control Systems utilize a controller or control actuator to obtain the desired response. Closed-Loop Control Systems utilizes feedback to compare the actual output to the desired output response. Multivariable Control System

Control System Classification Missile Launcher System

Open-Loop Control System

Control System Classification Missile Launcher System

Closed-Loop Feedback Control System

Control System Classification

Desired Output Response




Multi Input Multi Output (MIMO) System

Output Variables

Purpose of Control Systems i. Power Amplification (Gain) – Positioning of a large radar antenna by low-power rotation of a knob ii. Remote Control – Robotic arm used to pick up radioactive materials iii. Convenience of Input Form – Changing room temperature by thermostat position iv. Compensation for Disturbances – Controlling antenna position in the presence of large wind disturbance torque

Historical Developments i. Ancient Greece (1 to 300 BC) – Water float regulation, water clock, automatic oil lamp ii. Cornellis Drebbel (17th century) – Temperature control iii. James Watt (18th century) – Flyball governor iv. Late 19th to mid 20th century – Modern control theory

Control System Components i. System, plant or process – To be controlled ii. Actuators – Converts the control signal to a power signal iii. Sensors – Provides measurement of the system output iv. Reference input – Represents the desired output

General Control System Disturbance

Set-point or Reference input +

Controlled Signal




Manipulated Variable



Feedback Signal


+ +



Actual Output

Image acquisition and processingImage Processing Fields • Computer Graphics: The creation of images • Image Processing: Enhancement or other manipulation of the image • Computer Vision: Analysis of the image content

Image Processing Fields Input / Output




Image Processing

Computer Vision


Computer Graphics


Sometimes, Image Processing is defined as “a discipline in which both the input and output of a process are images But, according to this classification, trivial tasks of computing the average intensity of an image would not be considered an image processing operation

Computerized Processes Types • Mid-Level Processes: – Inputs, generally, are images. Outputs are attributes extracted from those images (edges, contours, identity of individual objects)

– Tasks: • Segmentation (partitioning an image into regions or objects) • Description of those objects to reduce them to a form suitable for computer processing • Classifications (recognition) of objects

Digital Image Definition • An image can be defined as a two-dimensional function f(x,y) • x,y: Spatial coordinate • F: the amplitude of any pair of coordinate x,y, which is called the intensity or gray level of the image at that point. • X,y and f, are all finite and discrete quantities.

Fundamental Steps in Digital Image Processing:

Colour Image Processing

Wavelets & Multiresolution processing

Image Compression

Image Restoration

Image Enhancement Image Acquisition

Problem Domain

Morphological Processing


Knowledge Base

Representation & Description

Object Recognition

Outputs of these processes generally are image attributes

Outputs of these processes generally are images

Fundamental Steps in DIP: (Description) Step 1: Image Acquisition The image is captured by a sensor (eg. Camera), and digitized if the output of the camera or sensor is not already in digital form, using analogue-to-digital convertor

Fundamental Steps in DIP: (Description) Step 2: Image Enhancement The process of manipulating an image so that the result is more suitable than the original for specific applications. The idea behind enhancement techniques is to bring out details that are hidden, or simple to highlight certain features of interest in an image.

Fundamental Steps in DIP: (Description) Step 3: Image Restoration - Improving the appearance of an image - Tend to be mathematical or probabilistic models. Enhancement, on the other hand, is based on human subjective preferences regarding what constitutes a “good” enhancement result.

Fundamental Steps in DIP: (Description) Step 4: Colour Image Processing Use the colour of the image to extract features of interest in an image

Fundamental Steps in DIP: (Description) Step 5: Wavelets Are the foundation of representing images in various degrees of resolution. It is used for image data compression.

Fundamental Steps in DIP: (Description) Step 6: Compression Techniques for reducing the storage required to save an image or the bandwidth required to transmit it.

Fundamental Steps in DIP: (Description) Step 7: Morphological Processing Tools for extracting image components that are useful in the representation and description of shape. In this step, there would be a transition from processes that output images, to processes that output image attributes.

Fundamental Steps in DIP: (Description) Step 8: Image Segmentation Segmentation procedures partition an image into its constituent parts or objects.

Important Tip: The more accurate the segmentation, the more likely recognition is to succeed.

Fundamental Steps in DIP: (Description) Step 9: Representation and Description - Representation: Make a decision whether the data should be represented as a boundary or as a complete region. It is almost always follows the output of a segmentation stage. - Boundary Representation: Focus on external shape characteristics, such as corners and inflections (‫)اﻧﺤﻨﺎءات‬ - Region Representation: Focus on internal properties, such as texture or skeleton (‫ )ھﯿﻜﻠﯿﺔ‬shape

Fundamental Steps in DIP: (Description) Step 9: Representation and Description - Choosing a representation is only part of the solution for transforming raw data into a form suitable for subsequent computer processing (mainly recognition) - Description: also called, feature selection, deals with extracting attributes that result in some information of interest.

Fundamental Steps in DIP: (Description) Step 10: Knowledge Base Knowledge about a problem domain is coded into an image processing system in the form of a knowledge database.

Components of an Image Processing System Network

Image displays


Mass storage


Specialized image processing hardware

Image processing software

Problem Domain

Image sensors

Typical generalpurpose DIP system

Elements of a Motion System Position App Software


Motion Controller

Current Amp/Drive

Feedback Device Position Feedback



Application Software App Software

Motion Controller


Feedback Device



Software Overview Configuration

Measurement and Automation Explorer


Motion Assistant

Application Development Environment

NI-Motion Driver for LabVIEW, Measurement Studio, C/C++ Visual Basic

Configuring a Motion Control System • Measurement & Automation Explorer – Use to configure all National Instruments devices – Tune servo motors – Test configuration – Configure signal routing – Test NI vision and data acquisition devices

NI-Motion Driver Software • For Windows and LabVIEW Real-Time Systems – VIs and functions for LabVIEW, Visual Basic, and C – Measurement and Automation Explorer • Configuration of motion and other components • Motor Tuning

• For Non-Windows Systems – Motion Control Hardware DDK – Linux and VxWorks drivers from Sensing Systems (www.sensingsystems.com)

NI Motion Assistant Prototyping Software

Configurable • Easy to use • Interactive • No programming required

Programmable • Flexible • Easier integration with other components

Purpose of the Motion Controller • Calculate the trajectories for each commanded move on the board to prevent host computer interference • Provide the torque commands to the motor drive or amplifier • Monitor limits and emergency stops for supervisory control • Close the PID loop

Motor Drive Requirements • The motor drive must match the motor technology – For example, 2-phase stepper motors require 2 phase stepper motor drives, etc… • The motor drive must provide adequate: – Peak current – Continuous current – Voltage

NI Motor Drive Products • MID series Stepper and Servo drives – MID-7604/2 four and two axis 1.4 Amp/phase stepper drive – MID-7654/2 four and two axis 5 Amp continuous servo drive • Universal Motion Interface (UMI) for easy connectivity to 3rd party drives • See Drive Advisor at ni.com/motion/advisors for info on third party drives

What is an Embedded System? • Computer purchased as part of some other piece of equipment – Typically dedicated software (may be user customizable)

– Often replaces previously electromechanical components – Often no “real” keyboard – Often limited display or no general purpose display device • But, every system is unique there are always exceptions

An Embedded Control System Designer's View • Measured by: Cost, Time to market, Cost, Functionality, Cost & Cost.

What is OPC • A “real world” application of object technology used to devise a standard communication system to enable industrial plant floor devices and business software applications to communicate via a standard common protocol.

Communication • Communication and integration of plant information systems: – Many different plant floor devices and process control software applications from many different vendors – Business Information and Management software

Information Islands Business Management

Plant Floor and Automation Devices

Process Management

A Better Way: OPC • The OPC Standard now places the burden on hardware vendors to develop a single OPC “driver” (server) that is responsible for data collection and distribution for their device(s). • Provide data to clients in a standard manor.

Client / Server Relationship • Software developers can now write clients that can communicate with hardware OPC servers using a common, efficient protocol OPC Server Vendor A

OPC Client #1

OPC Server Vendor B

OPC Server Vendor C

OPC Client #3

OPC Client #2

Technology (TLA Guide) • COM - Component Object Model – Provides objects as reusable, binary components – objects “expose” a set of interfaces that client applications can use to access the object’s services. – Implementation is encapsulated behind interfaces (allows object to change without requiring client recompilation)

Technology (continued) • DCOM - Distributed Component Object Model – remote objects appear to be local • OLE - Object Linking and Embedding – based on COM (e.g. an OLE object implements certain COM interfaces) – provides integration among applications

Technology (continued) • OLE Automation – Allows components to easily be used by high level custom programs (e.g. written in VB or VBA) – Set of special COM interfaces • automation or ActiveX objects implement these “automation” interfaces

– Automation Controllers • Clients that can integrate those objects

OPC and COM • OPC Specifications contain defined COM interfaces • Server and Client Interfaces – Data Access – Historical Data – Alarms and Events – etc. • Implementation and development

HMI /SCADA (Supervisory Control and Data Acquisition) System

What is SCADA?  Supervisory Control and Data Acquisition  Supervisory  Operator/s, engineer/s, supervisor/s, etc  Control  Monitoring  Limited  Telemetry  Remote/Local  Data acquisition  Access and acquire information or data from the equipment  Sends it to different sites through telemetry  Analog / Digital

Elements of SCADA Elements of a SCADA system  Sensors and actuators  RTUs/PLCs  Communication  MTU  Front End Processor  SCADA server  Historical/Redundant/Safety Server  HMI computer  HMI software

SCADA server SCADA Server  It can be a Web server  Data logging  Analyzing data  Serve the clients through a firewall  Clients connected in the corporation or connected outside through internet  Real-time decision maker  Asks RTU for information

HMI Computer Human Machine Interface Computer  Access on the SCADA Server  Control the system  Operator Interface  Software  User friendly  Programmable (C, C++)

DCS DCS – Distributed Control System  Process oriented – tendency to do something  Not event oriented – does not depend on circumstances  Local control over the devices  Subordinate to SCADA