Evolutionary design of fuzzy system for various problems including vision based mobile robot control

In this paper, a new evolutionary scheme for designing fuzzy logic system is proposed. We have developed a new fitness function for optimizing membership functions of antecedent parts of FLS. The proposed fitness function considers not only mean squared error, but also calculates some penalty based on the overlapping degree of adjacent membership functions for the same input. Consequent parts of the FLS are calculated using pseudo-inverse method. To show the effectiveness of the proposed algorithm, we have applied the proposed algorithm to various problems: Iris classification problem, Mackay-Glass time-series prediction problem and vision-based mobile robot control problem. It has been proven that, without much modification, the proposed algorithm can be used in various problem fields efficiently.