Design of Fuzzy Controller for Car Parking Problem Using Evolutionary Multi-objective Optimization Approach

This paper proposes an automatic method to design a fuzzy logic controller for the automated car parking problem within the multi-objective evolutionary optimization framework, which requires three factors: an encoding scheme, design of evaluation criteria, and design of evolutionary operations. Parameters of antecedent membership functions and consequent parameter vectors are encoded into a chromosome so that antecedent/consequent parameters and rule structure of a fuzzy logic controller are optimized simultaneously during evolution. Three optimization criteria are proposed to find a set of good fuzzy logic controllers using Pareto optimality. The proposed algorithm is applied to the well-known car parking problem and produced a Pareto set of fuzzy logic controllers that can control the motion of a vehicle for automated parking. Each fuzzy logic controller in the set has unique characteristics and can be selected according to users´ preferences, which is one of the major advantages of using the multi-objective evolutionary optimization