A.J. v a n d e r W a l *
European Technical Centre, Omron Europe B.V. Zilverenberg 2, 5234 GM “s-Hertogenbosch, Netherlands
In this paper an overview is given of the various ways fuzzy logic can be used to improve industrial control. The application of fuzzy logic in control is illustrated by two case studies. The first example shows how fuzzy logic, incorporated in the hardware of an industrial controller, helps to finetune a PID controller, without the operator having any a priori knowledge of the system to be controlled. The second example is from process industry. Here, fuzzy logic supervisory control is implemented in software and enhances the operation of a sintering oven through a subtle combination of priority management and deviation-controlled timing. Finally the key areas of research in fuzzy logic
control are discussed: First the paper discusses how fuzzy logic control can be combined with other methods. By properly separating the a priori model knowledge of the process under control, a hierarchy of nonlinear control methods is established. After a short discussion of how to optimize an intuitive fuzzy rule base, we show that it is possible to derive conditions for asymptotic stability and robustness of fuzzy logic controllers, using classical nonlinear analysis.
Keywords: Nonlinear control; Fuzzy logic; Neural networks; Genetic algorithms
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