Nonlinear sliding mode control design approach based on neural network modelling

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作者
Control Systems Research, Department of Engineering, University of Leicester, Leicester LE1 7RH, United Kingdom [1 ]
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来源
Int J Robust Nonlinear Control | / 7卷 / 397-423期
关键词
Backpropagation - Computer simulation - Control system synthesis - Errors - Neural networks - Robustness (control systems);
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摘要
A complete nonlinear framework for the modelling and robust control of nonlinear systems is proposed. The use of neural networks for continuous time modelling to obtain a certain nonlinear canonical form is investigated. The model obtained is used with recently proposed dynamic sliding mode controller design methods. The robustness bounds needed for controller design are determined from modelling errors. A modified version of the backpropagation theorem is also introduced.
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