An intelligent control system based on multiobjective genetic algorithms and fuzzy neural network

Abstract

A novel approach to intelligent control systems is proposed. It has three main functions: the fuzzy neural network controller, the performance evaluator, and the decision maker, which is to explore new actions to enhance control performance. The multiobjective genetic algorithm is presented to implement the adaptive mechanism to explore the new actions. The simulation results of robotic path planning showed the robot could reach the target point without collisions in various environments.