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Identification and Control of Dynamical System Using Neural Networks

This paper investigates the identification of discrete time nonlinear system using neural networks with two hidden layers. A New learning method of both NNI and NNC is proposed. For control of the dynamical system we use two neural networks, one for identification and the other for control, and proposed NN control system is based on a framework of MRC. We define a closed loop error. In the proposed learning method, the identification error and the closed loop error are utilized to train the NNI, whareas the control error and the closed loop error are used to train the NNC, The simulation results show that the identification and control schemes suggested are practically feasible and effective.