Multiple Designs of Fuzzy Controllers for Car Parking Using Evolutionary Algorithm

This paper proposes an automatic method to design a fuzzy logic multiple controllers for the automated car parking problem. To tackle the problem, design of a fuzzy logic controller is solved using multi-objective evolutionary optimization framework, which requires three factors: an encoding scheme, design of multi-objective evaluation criteria, and design of proper evolutionary operations. Along with the parameters of antecedent membership functions, consequent parameter vectors are defined in a chromosome so that a fuzzy logic controller can modify its antecedent/consequent parameters and rule structure simultaneously during evolution. Three optimization criteria are proposed to find a set of good fuzzy logic controllers using Pareto optimality.