An Optimal Fuzzy Neural Network Controller Based on Artificial Immune Principle

A design scheme of optimal RBF fuzzy neural network controller is proposed based on artificial immune principle. The structure of the controller is given, then the immune evolutionary algorithm is used to optimize the parameters of the controller to design an optimal RBF fuzzy neural network controller that satisfies quadratic performance index. The designed controller is employed to control an actual inverted pendulum system, and the scheme of state variable synthesis is used to reduce the number of fuzzy rules greatly. Experiment results has verified the effectiveness of the designed controller.