Adaptive Neural Network Robust Output Feedback Control for a Class of Uncertain Nonlinear System

Rickey Dubay and Jinzhu Peng


Neural network, Sliding mode control, H performance, Nonlinear system


A robust output feedback hybrid control scheme based on neural network for uncertain nonlinear system is proposed. The neural network is used to approximate the unknown ideal feedback control law of uncertain nonlinear system. Sliding model controllers are designed to eliminate the reconstruction errors and approximation errors of the neural network, and H controller is performed to achieve a certain robust tracking performance. It is proven that the signals in closed-loop are bounded and a specified H tracking performance is ensured by employing the proposed hybrid controller. Simulation results demonstrated that the proposed controller performed better in comparison to other advanced schemes.

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