Abstract:

For the problem that the uncertain upper bound value must be known in the general sdudy of sliding mode control, the upper bound adaptive dynamic SM（Sliding Mode) control method based on NN(Neural Networks) is proposed. Uncertainty and disturbance of the systems are separated from the systems to construct a conjoint upper boundary of the uncertainty. The process was  analysed in two steps. When the conjoint upper bound is known, the dynamic SM controller is designed.Otherwise the NN are adopted to learn adaptively the upper bound of the uncertainty. The rule of the weight adjustment and dynamic neural sliding mode controller are designed. The stability of the systems is investigated by constructing Lyapunov function. The controller can ensure the systems asymptotic stability. And it reduces the theory analysis condition of the SM control. It can also suppress the chattering effectively. The simulation examples show that the proposed dynamic neural sliding mode controller is correct and effective.

Key words: dynamic sliding mode, neural networks, upper bound adaptive, uncertain, nonlinear