Sum normal optimization of fuzzy membership functions
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Training fuzzy systems with the extended Kalman filter
Fuzzy Sets and Systems - Fuzzy systems
An add-on type fuzzy controller for control system retrofit
International Journal of Knowledge-based and Intelligent Engineering Systems
A new adaptive fuzzy controller with saturation employing influential rule search scheme (IRSS)
International Journal of Knowledge-based and Intelligent Engineering Systems
Optimization of rational-powered membership functions using extended Kalman filter
Fuzzy Sets and Systems
Designing fair flow fuzzy controller using genetic algorithm for computer networks
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
H∞ estimation for fuzzy membership function optimization
International Journal of Approximate Reasoning
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In this paper, an approach of designing adaptive fuzzy controllers is presented to systematically develop efficient and effective rules for fuzzy controllers. The proposed fuzzy controllers are first designed with two basic fuzzy if-then rules. Then according to the design requirements of the fuzzy control system, new fuzzy if-then rules are inserted into the rule-base structure of the fuzzy controller. Initially the inserted fuzzy rules are redundant in the sense that the resultant input-output mapping of the fuzzy rules remains intact. After that the parameters of the membership functions for the fuzzy sets of the newly added fuzzy rules are trained on-line to minimize predefined cost functions. Thus, efficient fuzzy controllers can be systematically designed. Simulations for linear, nonlinear, and delayed systems are provided to show the effectiveness of the proposed approach