The Research On Integrating Of Fuzzy Control, Neural Networks & Variable Structure Control And Its Application

Fuzzy system and artificial neural network are two of the successful directions in intelligent control. The research of intersection and integration of fuzzy control and artificial network has become one of the popular areas in automation, and a lot of significant achievement is got in fuzzy neural network (FNN). The embedded theory and application research in FNN is much significant for promting the application of intelligent control in productive practice and increasing the rate of production.On the basis of summarization of fuzzy control and neural network in domestic and abroad, their intersection and integration gives rise to FNN is proposed in the paper. Many kinds of FNN and their application are discussed. The mechanism of FNN is analyzed. It can not only bring into full play the superiority complment of fuzzy control and neural network but also overcome their shortcomeing.There still exists difficulty in FNN, such as the network performace is not so good, the efficiency of learning is not ideal, it is difficult to select optimal network structure, and even it may fall into local extreme value. Fuzzy neural network with structure learning (SL_FNN) is applying to promote the performance of network. The structure and learning algorithm of SLFNN is fully discussed, and SLFNN control system is obtained. The structure learning algorithm of three-layer and mutiple-layer SL_FNN is proposed.The mechanism of SLFNN is explained in the paper. The comparison with the brain of human being gives rise the control strategy and learning principle of SLFNN. The learning method from rough to fine is the essential characteristic of the learning process of SL_FNN. The superiority of SLFNN is that nerwork structure learning is achieved, and optimal one is reached. It overcomes the uncertainty of selecting network structure just by design experiment, and increases the FNN learning convergence velocity.