Identification and control of dynamical system by one neural network

The paper proposes a new neural control scheme that can perform identification and control for a dynamical system with linear and nonlinear uncertainties. This scheme uses a single neural network for both the identification and the control. By using the Lyapunov stability technique, stability of the proposed scheme is analyzed and a sufficient condition of the local asymptotic stability is derived. Then, a computer simulation is performed in order to illustrate the effectiveness and the applicability of the proposed scheme.