barcode reader using c#.net This may be reduced algebraically to the form given by Eq. (18.21) with in Software

Creating Code 128C in Software This may be reduced algebraically to the form given by Eq. (18.21) with

This may be reduced algebraically to the form given by Eq. (18.21) with
Code 128A Decoder In None
Using Barcode Control SDK for Software Control to generate, create, read, scan barcode image in Software applications.
Painting Code 128B In None
Using Barcode generation for Software Control to generate, create Code 128 Code Set A image in Software applications.
27 + 2(A +
Decode Code 128 Code Set C In None
Using Barcode reader for Software Control to read, scan read, scan image in Software applications.
Printing Code 128 Code Set C In C#.NET
Using Barcode printer for VS .NET Control to generate, create Code 128 Code Set B image in VS .NET applications.
7 + rrd
Making Code 128B In VS .NET
Using Barcode printer for ASP.NET Control to generate, create Code 128C image in ASP.NET applications.
Code 128A Printer In VS .NET
Using Barcode printer for VS .NET Control to generate, create Code 128 Code Set B image in Visual Studio .NET applications.
Td Td) (Td/2)
Code 128A Drawer In Visual Basic .NET
Using Barcode creation for .NET framework Control to generate, create Code 128C image in Visual Studio .NET applications.
Generating Barcode In None
Using Barcode generator for Software Control to generate, create bar code image in Software applications.
71 =
ECC200 Creator In None
Using Barcode generator for Software Control to generate, create ECC200 image in Software applications.
Generate Barcode In None
Using Barcode maker for Software Control to generate, create barcode image in Software applications.
TO = 27 + rd
Code 128 Code Set B Encoder In None
Using Barcode creation for Software Control to generate, create Code 128 Code Set A image in Software applications.
Encode GTIN - 128 In None
Using Barcode generation for Software Control to generate, create EAN / UCC - 13 image in Software applications.
" = 2(h + 7d)
EAN-8 Supplement 2 Add-On Printer In None
Using Barcode drawer for Software Control to generate, create EAN8 image in Software applications.
Bar Code Drawer In Java
Using Barcode maker for Java Control to generate, create barcode image in Java applications.
The response of this first-order with transport lag system for several values of A and forK = 1, r = 1, rd = 1 isgiveninFig. 18.32. ThevaluesofK,, 71, rd, and71 obtained from the above relations are shown in Table 18.2. Notice that once a model is accepted, the tuning of the modified IMC controller [Eq. (18.21)] depends only on the choice of A. For the range of A used, Fig. 18.32 shows that the step response is only slightly oscillatory for all values of A and the fastest response is for A = 0.5. Also notice that A affects only K, and ~1. This example shows that the design of a controller by the IMC method is a straightforward procedure and leads to a controller that requires the adjustment of only one parameter, A.
Bar Code Maker In Visual C#
Using Barcode drawer for VS .NET Control to generate, create bar code image in .NET applications.
Make 2D Barcode In VS .NET
Using Barcode creation for ASP.NET Control to generate, create Matrix Barcode image in ASP.NET applications.
PROCESS
Recognizing UCC.EAN - 128 In C#.NET
Using Barcode scanner for .NET framework Control to read, scan read, scan image in .NET applications.
Creating Barcode In Java
Using Barcode generator for Android Control to generate, create bar code image in Android applications.
APPLICATIONS
USS Code 39 Encoder In Visual C#
Using Barcode generator for .NET Control to generate, create Code 39 image in VS .NET applications.
Decode Code39 In VB.NET
Using Barcode scanner for .NET framework Control to read, scan read, scan image in .NET applications.
2.0 1.80 1.60
18-32
FIGURE
Response for IMC-designed controller of Example 18.6.
It is instructive to compare the response for the IMC-derived controller with the response for a PI controller using Ziegler-Nichols settings. The responses, which are given in Fig. 18.33, show that for this particular example the controller using Z-N settings produces a response with less overshoot and a higher frequency of oscillation than the controller designed by the IMC method. These two examples show clearly how the parameters of the conventional controller G, are related to the parameters of the model and the filter. The treatment of internal model control presented here has been limited to single input/single output continuous systems for which the disturbance is a step change. Furthermore, we have not discussed the use of model uncertainty in selecting the filter parameters. Internal model control has been extended to sampled-data control systems and to multiple input/multiple output systems. IMC is a new approach to the design of control systems that considers the process model as an essential part of the control system design. As the method becomes better understood it will most likely affect the design of industrial control systems. Microcomputer-based controllers now have the capability of implementing many of the control algorithms designed by the IMC method. There is no longer a need to be tied to the classical control algorithms.
TABLE 18.2
IMC derived controller settings for Example 18.6
A KC 71
0.75 1.5 0.33 0.25
1.5 0.33 0.30
1.5 0.33 0.167
1.5 0.33 0.33
ADVANCED CONTROL STRATEGIES
21.8 1.6 1.4 o 1.2 1.0 .8 .6 .4 .2 0.0 0
FIGURE 18-33 Comparison of response for IMC controller and conventional controller for Example 18.6: I IMC-derived controller with A = 1.0, II PI controller with Ziegler-Nichols settings (K, = 1.02, q = 2.84).
SUMMARY
In this chapter, we have examined five advanced control strategies. The first three on cascade control, feedforward-feedback control, and ratio control are advanced only in the sense that each strategy is more complex than the single-loop systems we have encountered up to this chapter. These three strategies are used extensively in industry and modern microprocessor-based controllers can implement them easily. The other strategies, on Smith prediction and internal model control (IMC), are less likely to be used in industry and are closely related in their block diagram structure. Of the five control strategies, the IMC method has the most rigorous mathematical foundation and is presently the focus of intense academic research. Three of the strategies, feedforward-feedback, Smith prediction, and IMC, are dependent on accurate models of the processes for their application. Cascade control is especially useful in reducing the effect of a load disturbance that is located far from the control variable and which moves through the system slowly. The presence of the inner control loop reduces the lag in the outer loop with the result that the cascade system responds more quickly to a load disturbance. If a particular load disturbance occurs frequently, the quality of control can often be improved by applying feedforward control. Ideally the transfer function of the feedforward controller is obtained from knowledge of the model of the process. In cases where the feedforward controller transfer function requires prediction (for example rfs + I), one must be satisfied with an approximation of the feedforward controller, which takes the form of a lead-lag transfer function. When a model of the process does not exist, the feedforward controller can be tuned after doing some open-loop step tests that relate the control variable to the load disturbance. To provide for load disturbances that cannot be measured or anticipated, feedforward control is always combined with feedback control in a practical situation. Ratio control is widely used in industry in the blending of two component streams (A and B) to produce a mixed stream of desired composition (i.e., ratio of components). Ratio control is essentially a flow-control problem in which
Copyright © OnBarcode.com . All rights reserved.