A learning algorithm of fuzzy rules using GA for MRACS with time-delay
K. Shida, H. Ochia, H. Fujikawa, Shinichi Yamada · 2002
By use of fuzzy reasoning, MRACS can be applied to nonlinear systems. Genetic algorithms can be used to get optimal control rules automatically. These rules are remarkably better than hand-constructedones, but the optimizing procedure is time-consuming. In this paper, we try three techniques to simplify the adaptive rules and obtain quasi-optimal parameters rapidly.>