Optimal design of radial basis function fuzzy neural network controllerbased on immune evolutionary algorithm
采用免疫进化算法优化设计径向基函数模糊神经网络控制器

The computational intelligence based on biology immune system is becoming the focal point in recent years.Aiming at the design difficulty for fuzzy neural network controller,an immune evolutionary algorithm is proposed to design the parameters of a radial basis function fuzzy neural network controller.First,the parameters of the controller were encoded into an individual,and the initial population was composed of some random individuals; then,simulating the process of biology adaptive immune response,expansion operation was used to perform local searching in a small neighborhood of the better individuals in population,and mutation operation was used to search in a large neighborhood of the worse individuals.Finally,the designed controller was employed to control an inverted pendulum system,and the simulation results verified the effectiveness of the controller.