A method of automatically extracting and optimizing fuzzy rule base is presented in this paper. Firstly, it applies the method of CCM (cell-to-cell mapping) to analyze the evolving trend and global behavior of a fuzzy dynamical system based on a cell state space, which is characterized by equilibrium, cost and their domain of attractions. Secondly, each rule base is evaluated to determine a performance index based on the information of the system obtained by CCM. Thirdly, CA (Genetic Algorithm) optimizes the coded rule bases according to the performance index generation by generation. The method presented in this paper can be applied to various systems (linear or nonlinear, continuous or discrete) to automatically obtain optimal rule base, for it fuses the advantages of GA and CCM. As an example, a complicated nonlinear system-an inverted pendulum is simulated to demonstrate the validity of the method.
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