Research Of Fuzzy Neural Network Control Method Of A Kind Of Non-linear System

Fuzzy system and artificial neural network are the important developing directions of the intellectual control theory. They have the obvious mutual complementarity, which accelerated fuzzy logic and artificial neural network forming a new research direction. The combination of the fuzzy logic and artificial neural network is the fuzzy neural system. It has the important theory meaning and the actual application value to use it in the research of complicated non-linear system. It has been widely used in the automatic controlled field. This paper mainly focused on the problem of fuzzy neural network control of non-linear system and got into further study and then a self-adaptation control system of fuzzy neural network was designed. In my paper, the fuzzy counter-propagation network was used to identify the objects and the controller was designed based on RBF network. The mixing algorithm was adopted to optimize and train the two networks. I combined the fuzzy neural system and the self-adaptation control scheme together and used the designed identification device and controller to design a self-adaptation controlling system of the fuzzy neural network which can effectively control the non-linear system. Using the non-linear system as the controlled object, the feasibility and validity of the project in my paper is proved by lots of simulation experiments.