PID Controllers, 2nd Edition

Chapter 7.10 - Control Paradigms: Conclusions

In this chapter we have illustrated how complex control systems can be built from simple components such as PID controllers, linear filters, gain schedules, and simple nonlinear functions. A number of control paradigms have been introduced to guide system design.

The primary linear control paradigms are feedback by PID control, and feedforward. Cascade control can be used to enhance control performance through the use of extra measurements. Observers can be used in a related way when measurements are not available. Control by observers and state feedback may be viewed as a natural extension of cascade control.

Smith predictors (discussed in Section 3.9) can be used to improve control of systems with long dead time, and notch filters and other filters with complex poles and zeros are useful when controlling systems with poorly damped oscillatory modes.

We also discussed several nonlinear components and related paradigms. The nonlinearities used are nonlinear functions, gain schedules, limiters, and selectors. In Section 3.4, how simple PID controllers could be enhanced by simple nonlinear functions was discussed. This was used to avoid windup and to provide special control functions like "error squared on integral," etc. Ratio control is a nonlinear strategy that admits control of two process variables so that their ratio is constant. In Section 6.3 we discussed how gain schedules could be used to cope with control of processes with nonlinear characteristics. Gain schedules and nonlinear functions are also useful for control paradigms such as surge tank control, where the goal is not to keep process variables constant but to allow them to vary in prescribed ranges. Selector control is another very important paradigm that is used for constraint control where certain process variables have to be kept within given constraints. We also showed that controllers based on neural and fuzzy techniques could be interpreted as nonlinear controllers.

Parameter estimation, discussed in Section 2.7, can be used to estimate process parameters. Adaptation and tuning are other paradigms that were discussed in Chapter 6.

There are many ways to use the different control paradigms. We have also indicated that there may be difficulties due to interaction of several loops.

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