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Abstract

The objective of fuzzy logic control (FLC) systems is to control complex processes by means of human experience. Thus fuzzy control systems and expert systems both stem from the same origins. However, their important differences should not be neglected. Whereas expert systems try to exploit uncertain knowledge acquired from an expert to support users in a certain domain, FLC systems as we consider them here are designed for the control of technical processes. The complexity of these processes range from cameras [Wakami and Terai 1993] and vacuum cleaners [Wakami and Terai 1993] to cement kilns [Larsen 1981], model cars [Sugeno and Nishida 1985], and trains [Yasunobu and Miamoto 1985]. Furthermore, fuzzy control methods have shifted from the original translation of human experience into control rules to a more engineering-oriented approach, where the goal is to tune the controller until the behavior is sufficient, regardless of any human-like behavior.

Keywords

Membership Function Fuzzy Control Fuzzy Controller Linguistic Variable Fuzzy Logic Control 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • H.-J. Zimmermann

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