Adaptive Neural Network Control with Unknown Dead-Zone and Gain Sign

The problem of adaptive control for a class of SISO nonlinear systems with unknown non-symmetric dead-zone and unknown control gain sign is studied in this paper. Based on the principle of sliding mode control and the property of Nussbaum function, two design schemes of adaptive neural network controller are proposed. By introducing characteristic function for the dead-zone model in the systems, a simplified dead-zone model is developed. The approach removes the condition of the equal slope with defined region. The adaptive compensation term of the approximation error is adopted to minify the influence of modeling errors and parameter estimation errors. By theoretical analysis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded.