## A Course in Fuzzy Systems and ControlProvides a comprehensive, self-tutorial course in fuzzy logic and its increasing role in control theory.The book answers key questions about fuzzy systems and fuzzy control. It introduces basic concepts such as fuzzy sets, fuzzy union, fuzzy intersection and fuzzy complement. Learn about fuzzy relations, approximate reasoning, fuzzy rule bases, fuzzy inference engines, and several methods for designing fuzzy systems.For professional engineers and students applying the principles of fuzzy logic to work or study in control theory. |

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### Contents

The Mathematics of Fuzzy Systems and Control | 19 |

Further Operations on Fuzzy Sets | 34 |

Fuzzy Relations and the Extension Principle | 48 |

Copyright | |

29 other sections not shown

### Common terms and phrases

a-cuts adaptation law adaptive fuzzy control approach approximate approximation error cement kiln center average defuzzifier Chapter choose closed-loop system cluster compute converges defined Definition demonstrated the following denoted design the fuzzy designed fuzzy system determine Dienes-Rescher direct adaptive fuzzy dynamic TSK fuzzy equation example Figure fuzzy complement fuzzy control system fuzzy IF-THEN rules fuzzy inference engine fuzzy logic fuzzy numbers fuzzy propositions fuzzy relation fuzzy rule base fuzzy set fuzzy theory Gaussian ha(x Hence hypothetical syllogism input input-output pairs intuitive inverted pendulum Lemma linear programming linear programming problem linguistic variables Lukasiewicz Lyapunov maximum defuzzifier membership functions membership value method modus ponens modus tollens nonlinear system number of rules obtain operators output phase plane PID controller product inference engine Proof recursive least squares shown in Fig singleton fuzzifier sliding control stable Step Summary and Further supervisory controller t-norm Theorem trajectory TSK fuzzy system vector Zadeh zero