Identification and Control for Discrete Dynamics Systems using Space State Recurrent Fuzzy Neural Networks

This work presents a structure for modelling and control non linear systems based upon states space recurrent fuzzy neural network (SSRFNN). SSRFNN model has space state structure which is identified since input output data. Fuzzy rules are automatic added through cluster method. Consequent parameter are estimated by using time backpropagation algorithm. An extra observer algorithm is design in order to obtain necessary states measurements. There after control strategy is proposed they some multiple interconnected systems.