Control And Design Simulation Module Labview

[Chloe Sarnoff]

Ihave both LabVIEW 2013 64-bit and 2014 64-bit editions. I downloaded the "Control Design & simulation" module for both versions. However, it doesn't work. When I bring up the "controls" panel in the Front Panel or the "Functions panel in the Block Diagram and click on "Control Design & Simulation" tab, I find it empty. The LabVIEW components window shows that the CD Sim is already installed and acitivated. I attached a picture to explain what's wrong.

I believe the Control Design & Simulation module is only compatible with LabVIEW 32-bit. This is the case with most LabVIEW modules. My suggestion would be to install 32-bit LabVIEW on 64-bit Windows, which is the most common configuration for using NI software.

As described there, the Control Design and Simulation module is not compatible with LabVIEW 64-bit software (as are a lot of the other drivers and toolkits). I would recommend installing LabVIEW 32-bit instead!

I have installed Labview 2017 32 bit in my PC. It is showing control and Simulation. It contains only PID and Fuzz logic Controllers. It doesn't contain any Simulation, Control Design and System Identity. How can i get them?

The introduction is based on simple examples - all downloadable via hyperlinks. Only the basic functions are demonstrated. You can search for a function via the Help menu in LabVIEW or just browse for it on the Control Design palette in the Functions palette in LabVIEW. Chapter 2 of this document list all functions available in the Control Design Toolkit.

Note that many of the functions on the Control Design Palette have similar functions in MathScript (once the Control Design toolkit is installed). The Control Design class of functions in MathScript are shown at the end ofIntroduction to MathScript.

Each function has several input parameters or arguments. You should always use Help (via right-clicking on the function block) to get information about these parameters before you use the function in your program.

The Control Design Toolkit was initially launched in Spring 2004. It expands LabVIEW's capabilities for control system and dynamic system analysis and design considerably. The set of functions available is comparable with the Control System Toolbox in Matlab and the similar control system function category in Octave.

Included in Control Design Toolkit is the Control Design Assistant, which is an interactive tool which can be used independent of LabVIEW, and without LabVIEW programming (you can however create LabVIEW code from your Control Design Assistant project). The Control Design Assistant is available from the Start / Programs / National Instruments meny on your PC and from the Tools / Control Design Toolkit in LabVIEW.

The VIs in the examples does not contain any while loops. Consequently, the VIs run just once. If you want a VI to run continuously with a well-defined time step between each while loop execution, possibly while you are adjusting some parameters, you can place the block diagram code in while loop.

The Model Construction palette contains several functions for creating models. The resulting model is represented as a cluster. This cluster can be used as input argument to other functions, e.g. for simulation, frequency response analysis, etc.

Once the model is created, you can simulate it using functions on the Time Response palette, and you can perform analysis, for example frequency response analysis using functions on the Frequency Response palette. Note that these simulation and analysis functions can be used on both continuous-time models and discrete-time models.

The VI shown below shows how to create and display an PID Academic controller (which is a standard parallel PID controller). (The derivative time is set to zero, so the controller is actually a PI controller.)

You can use models created in Control Design Toolkit in a Simulation diagram in theLabVIEW Simulation Module. However, it is then necessary to first convert the model by using the CD Convert Control Design to Simulation function.

In models of feedback control systems, transfer functions are connected in a feedback loop. The resulting transfer function can be calculated using theCD Feedback function. This functions works for continuous-time models and for discrete-time models.

Note: For continuous-time models, the CD Feedback function ignores a time delay included in any of the transfer functions in the feedback loop, that is, the resulting transfer function is derived assuming the time delays are zero. To actually include the time delay(s), use the CD Construct Special Model function with the option Delay (Pade Approx.) selected to create a rational transfer function representing (and approximating) the time delay. Then include this transfer function in the feedback loop using e.g. theCD Series function. This is demonstrated inExample 9.1.

The following example shows how to connect discrete-time transfer functions including time delays in a feedback loop. It is necessary to convert the time delay part of a discrete-time model to poles at the origin using the CD Convert Delay to Poles at Origin function for the CD Feedback function to produce the correct transfer function of the combined feedback loop. This also applies to discrete-time transfer functions which have been derived by discretizing an original continuous-time transfer function, that is, you have to use the CD Convert Delay to Poles at Origin function for the CD Feedback function to produce the correct result.

In the VI shown below two discrete-time transfer functions are connected in a feedback loop. One of the transfer functions, H2(z), contains a time delay of 2 samples, corresponding to 2 poles at the origin of the z-plane.

The CD Convert to Transfer Function Model function converts continuous-time and discrete-time state-space models to transfer function models. The resulting transfer function model is actually a MIMO (multiple input multiple output) transfer function, i.e. a transfer function matrix. To get a particular SISO (single input single output) transfer function from this MIMO transfer function you must apply theCD Get Data from Model function. This is illustrated in the following example. This example is about a continuous-time model, but the same functions are used for discrete-time models.

The following example illustrates how to discretize a continuous-time transfer function using the CD Convert Continuous to Discrete function. The same function can be used to discretize state-space models. Converting a model the opposite way - from discrete-time to continuous-time - is done in a similar way using the CD Convert Discrete to Continuous function.

The VI shown below shows how to do the discretization using the ZOH method (zero order hold) with sampling time 0.2s. The original transfer function contains a time delay of 1 second. This time delay is represented in the discrete-time transfer function by the factor z-5 (since 5*0.2s = 1s).

The VI shown below shows how to analyze and simulate a feedback control system. The block diagram code is put inside a while loop with cycle time 100ms to make the program run continuously. The controller is a PID Academic controller (which has parallel form) with the following transfer function, Hc(s):

Proportional Integral Derivative (PID) is one of the most commonly used control algorithms due its ease of use and minimal required knowledge of the system or plant to be controlled. NI provides ready-to-run, advanced (PID) control algorithms with the NI LabVIEW PID Control Toolkit. Combined with the LabVIEW Control Design & Simulation Module, which is part of LabVIEW Professional, the LabVIEW PID Control Toolkit can help you simulate and tune your PID controllers without implementing them in real-world systems, thus avoiding possible problems such as instability during application development. In this tutorial, learn how to use the LabVIEW PID Control Toolkit with the LabVIEW Control Design & Simulation Module and design the PID gains for the position controller of a DC motor in a Real-Time system.

In this tutorial, we will design the velocity controller for a DC motor. For the sake of simplicity consider a basic transfer function for a DC motor where effects such as friction and disturbances are being considered:

Figure 1. Create a Control & Simulation Loop.

Again on the Simulation subpalette, select Continuous Linear Systems and click once on Transfer Function and once inside the Control & Simulation Loop you created previously. This places a Transfer Function block inside the Control & Simulation Loop. Now double-click on the Transfer Function block to input the transfer function parameters.

Figure 4. Create an input signal using a step signal.

Now create the components necessary to view the simulation results. First bundle the input (Step Signal) with the output from the motor transfer function into a Build Array node, which you can find on the Programming->Arrays subpalette. Collect these signals and plot them on a graph on the Front Panel. To do so, select Control Design & Simulation->Simulation->Utilities then select and drop Collector. On the Front Panel, create an XY Graph to display the simulation results. Connect all the signals as shown in Figure 5.

Use LabVIEW native graphical capabilities to improve the simulation and fine-tune the PID gains.

First, change axis properties to have a better view of the simulation results. Right-click on the border of the XY Graph and uncheck the AutoScale X property under the X Scale option.

Figure 7. Graph properties.

Before making changes to the PID controller, we will make the simulation more efficient. As seen on Figure 6 there is no need to simulate the default 10 seconds; the plant is fast enough so that a final simulation time of 2 seconds is enough. Now modify the simulation parameters by double-clicking on the Control & Simulation Loop configuration pane which calls up the Configure Simulation Parameters dialog window. Implement the parameters as shown in Figure 8.

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