Abstract
A compound neural network is utilized to identify the dynamic nonlinear system. This network is composed of two parts: one is a linear neural network, and the other is a recurrent neural network. Based on the inverse theory a compound inverse control method is proposed. The controller has also two parts; a linear controller and a nonlinear neural network controller. The stability condition of the closed-loop neural network-based compound inverse control system is demonstrated based on the Lyapunov theory. Simulation studies have shown that this scheme is simple and has good control accuracy and robustness.
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