Systems and Control

Chapter 8: Fuzzy Systems

It is in the response to mistakes, of technique or of judgment, that one sees most clearly the human side of science's practitioners: a mix of pride, stubbornness, humility, honesty, dismay, and regret that one could expect to encounter in any section of the population. There are the inevitable diehards, whose pride forces them to concoct ever-more-elaborate explanations for the facts in order to avoid confession of error. There are the crusaders, determined at all costs to expose the foolishness. And there are the "told-you-so's," generally members of the scientific elite, who make little contribution while the debate is raging but are ready to heap scorn on the perpetrators afterward for their "obvious" mistakes. All this, of course, is the antithesis of objective science, but follows as inevitably as night follows day from the fact that science is practiced by people and not by automatons.

A Biography of Water: Life's Matrix [18, p. 291]

8.1 Motivation and Basic Definitions

Conventional control algorithms require a mathematical model of the dynamical system to be controlled. The mathematical model is then used to construct a controller. In many practical situations, however, it is not always feasible to obtain an accurate mathematical model of the controlled system. Fuzzy logic control offers a way of dealing with modeling problems by implementing linguistic, nonformally expressed control laws derived from expert knowledge. This approach is especially successful in the case of processes such as washing machines, camera focusing, or drying processes that are being...

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