Adaptive Neural Network Control Based on Trajectory Linearization Control

Abstract

In this paper, an adaptive neural network nonlinear control method is developed based on trajectory linearization control (TLC). The adaptive neural network TLC control (ANNTLC) compensates the model nonlinear uncertainty adaptively, and improves controller performance. ANNTLC can also be used to simplify the TLC control design procedure by using a simplified model. A stable neural network learning rule is developed. The simulation result shows the feasibility of the proposed method

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Cite this paper

@article{Liu2006AdaptiveNN, title={Adaptive Neural Network Control Based on Trajectory Linearization Control}, author={Yong Liu and Rui Huang and J . Jim Zhu}, journal={2006 6th World Congress on Intelligent Control and Automation}, year={2006}, volume={1}, pages={417-421} }