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Global Neural Dynamic Surface Tracking Control of Strict-Feedback Systems With Application to Hypersonic Flight Vehicle

Bin Xu, Chenguang Yang, Yongping Pan

IEEE Transactions on Neural Networks and Learning Systems, Volume: 26, Issue: 10, Pages: 2563 - 2575

Swansea University Author: Chenguang Yang

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DOI (Published version): 10.1109/TNNLS.2015.2456972

Abstract

In this paper, we investigate both indirect and direct global neural control of nonlinear systems in strict-feedback form. The dynamic surface control (DSC) technique is employed together with a novel switching mechanism, and neural approximation is utilized to compensate for the effect caused by un...

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Published in: IEEE Transactions on Neural Networks and Learning Systems
Published: 2015
URI: https://cronfa.swan.ac.uk/Record/cronfa27024
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Abstract: In this paper, we investigate both indirect and direct global neural control of nonlinear systems in strict-feedback form. The dynamic surface control (DSC) technique is employed together with a novel switching mechanism, and neural approximation is utilized to compensate for the effect caused by unknown dynamics. A robust term is integrated into the control design to pull the transient states back into the neural approximation domain when they go beyond. The proposed method ensures globally uniformly ultimately boundedness stability, in comparison to the conventional semiglobal stability achieved by most existing neural controllers. Simulation studies are performed on a hypersonic flight vehicle (HFV) model to verify the effectiveness of the proposed global neural controller.
College: College of Engineering
Issue: 10
Start Page: 2563
End Page: 2575