On GA-based Optimal Fuzzy Control

淡江大學機構典藏 > 文學院 > 資訊與圖書館學系暨研究所 > 會議論文 > Item 987654321/53599

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/53599

Title:	On GA-based Optimal Fuzzy Control
Authors:	Lin, Sinn-cheng;Chen, Yung-yaw
Contributors:	淡江大學資訊與圖書館學系
Keywords:	Fuzzy control;Optimal control;Fuzzy sliding-mode control;Genetic algorithms
Date:	1995-11
Issue Date:	2011-05-20 09:51:07 (UTC+8)
Abstract:	Two architectures for designing optimal fuzzy control systems were proposed in this paper. In both cases, the membership functions in the fuzzy rulebases were tuned by the genetic algorithms. The objective was to explore a fuzzy controller by minimizing a quadratic cost fkction. In the first architecture, the employed controller was a conventional, fuzzy logic controller which used the system states as input variables. Consequently, the reciprocal of the cost function to be minimized could be directly applied towards evaluating the fitness of the controller. In the second architecture, a $my sliding mode controller was adopted. The combined information of the system states, i.e. the sliding function, formed a single input variable. The problem of minimizing the cost function in this case could be transformed to that of deriving an optimal sliding surface. Then, a faster hitting time and a smaller distance away from the sliding surface a controller had, a lugher fitness it got. Simulations and comparisons were taken on both cases.
Relation:	IEEE International Conference on Evolutionary Computing, Perth, Australia
Appears in Collections:	[資訊與圖書館學系暨研究所] 會議論文

Files in This Item:

There are no files associated with this item.