Evolvable Hardware for Fuzzy Logic Controllers Design
Fuzzy Logic Controllers (FLCS) are rule-based systems that successfully incorporate the flexibility of human-decision making by means of the use of fuzzy set theory. This paper provides an overview on evolutionary learning methods for the automated design and optimization of fuzzy logic controllers. A three-stage evolution framework that uses Genetic Programming (GP) and Genetic Algorithms (GAS)evolves rule-base and membership function parameters of FLCS. For hardware implement of FLCS, We propose an Evolvable Hardware (EHW) platform for the design of fuzzy logic controllers. This platform, which can be used for the implementation of the designed fuzzy system, is based on a PAMA (Programmable Analog Multiplexer Array).The performance of a fuzzy system in the control of both a linear and a nonlinear function is evaluated. The results obtained with these functions show the applicability of this model in the design of fuzzy control systems.
Fuzzy logic controllers Evolvable Hardware Evolutionary algorithm
Dabin Zhang Yuanxiang Li
School of Computer, Wuhan University, Wuhan 430072, Hubei, China;Dept of Information Management, Hua School of Computer, Wuhan University, Wuhan 430072, Hubei, China
国际会议
杭州
英文
771-775
2006-10-12（万方平台首次上网日期，不代表论文的发表时间）