Adaptive control feedforward

While the single-loop PID controller is satisfactoiy in many process apphcations, it does not perform well for processes with slow dynamics, time delays, frequent disturbances, or multivariable interactions. We discuss several advanced control methods hereafter that can be implemented via computer control, namely feedforward control, cascade control, time-delay compensation, selective and override control, adaptive control, fuzzy logic control, and statistical process control. 

From previous experimental data we know how the optimal fuel/air ratio changes with air temperature for maximum efficiency. Therefore, to maintain the ratio continuously at its optimal value despite any changes in the air temperature, we can use a programmed adaptive control system. Such a system is shown in Figure 22.3b. It measures the temperature of the air (auxiliary measurement) and adjusts the value of the fuel/air ratio. Notice again that the ratio adjustment mechanism is like feedforward compensation. 

Although feedback control is the type encountered most commonly in chemical processes, it is not the only one. There exist situations where feedback control action is insufficient to produce the desired response of a given process. In such cases other control configurations are used, such as feedforward, ratio, multivariable, cascade, override, split range, and adaptive control. 

As discussed in Chapter 21, the effectiveness of a feedforward control loop depends heavily on the quality of the model available for the process. Develop an adaptive control mechanism for a feedforward controller which will compensate for any variations in the model of the process. 

An important observation is that any control program may be followed, even one that would cause the process gain dc/dm to change sign. Hence feedforward is the logical means to achieve optimizing (steady-state adaptive) control. This has already been demonstrated in Chap. 6. 

Owing to this nonlinearity, as well as to the problems mentioned earlier, some exothermic reactors are controlled with advanced control techniques, such as feedforward, model reference or adaptive control [11]. 

Part V (Chapters 19 through 22) deals with the description, analysis, and design of more complex control systems, with one controlled output. In particular, Chapter 19 introduces the concept of feedback compensation with Smith s predictor, to cope with systems possessing large dead times or inverse response. Chapter 20 describes and analyzes a variety of multiloop control systems (with one controlled output) often encountered in chemical processes, such as cascade, selective, and split-range. Chapter 21 is devoted exclusively to the analysis and design of feedforward and ratio control systems, while Chapter 22 makes a rather descriptive presentation of adaptive and inferential control schemes why they are needed and how they can be used. 

How can we use the tremendous computational power of a computer to implement some advanced notions of process control, such as feedforward, adaptive, inferential, optimizing, and so on ... 

On-line adaptation is not limited to feedback systems. On-line process identification can be coupled easily with feedforward, inferential, and other control systems, thus expanding the range of their applicability. Adaptation is particularly valuable for feedforward and inferential systems because they rely heavily on good process models for their successful implementation. 

Describe an on-line adaptive procedure for a typical feedforward control system (see Chapter 21). Do the same for the inferential control of a distillation column (see Example 22.S). 

Abbas, J.J. and Triolo, R.J. 1997. Experimental evaluation of an adaptive feedforward controller for use in functional neuromuscular stimulation systems. IEEE Trans. Rehabil. Eng., 5 12—22. 

Figure 10.14 showed a combined feedforward-feedback control system with a forward loop from flow only. In waste-treating systems, the pH of the stream to be neutralized often varies more than its flow. But because the relationship between pH and reagent requirement is variable, adaptation of the forward loop by feedback is essential. 

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