A Robust Neural Controller for a Class of Second-Order Nonlinear Systems

A Robust Neural Controller for a Class of Second-Order Nonlinear Systems hihong Man, A. P. Paplinski and H. R. Wu
Abstract
	A robust adaptive neural controller for a class of second-order nonlinear systems is proposed in this paper. It is shown that the terminal sliding mode control technique can be used in the design of the neural controller. The weights of the neural network can be adaptively adjusted for the compensation of uncertain dynamics and the tracking error between the plant output and the model output can be guaranteed to converge to zero in a finite time.

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