Gain-scheduled H∞ control via parameter-dependent Lyapunov functions

Date published

2013-03-08

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Taylor & Francis

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Article

ISSN

0020-7721

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Citation

Chumalee, S., Whidborne, J. F. (2013) Gain-scheduled H∞ control via parameter-dependent Lyapunov functions, International Journal of Systems Science, Vol. 46, Iss. 1, pp. 125 - 138

Abstract

Synthesising a gain-scheduled output feedback H∞ controller via parameter-dependent Lyapunov functions for linear parameter-varying (LPV) plant models involves solving an infinite number of linear matrix inequalities (LMIs). In practice, for affine LPV models, a finite number of LMIs can be achieved using convexifying techniques. This paper proposes an alternative approach to achieve a finite number of LMIs. By simple manipulations on the bounded real lemma inequality, a symmetric matrix polytope inequality can be formed. Hence, the LMIs need only to be evaluated at all vertices of such a symmetric matrix polytope. In addition, a construction technique of the intermediate controller variables is also proposed as an affine matrix-valued function in the polytopic coordinates of the scheduled parameters. Computational results on a numerical example using the approach were compared with those from a multi-convexity approach in order to demonstrate the impacts of the approach on parameter-dependent Lyapunov-based stability and performance analysis. Furthermore, numerical simulation results show the effectiveness of these proposed techniques.

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Github

Keywords

Gain-scheduling control, Parameter-dependent Lyapunov functions, Linear parameter-varying systems, Linear matrix inequality, Nonlinear control, Robust control

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Attribution-Non-Commercial 3.0 Unported (CC BY-NC 3.0) You are free to: Share — copy and redistribute the material in any medium or format, Adapt — remix, transform, and build upon the material. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Information: Non-Commercial — You may not use the material for commercial purposes. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
This is a postprint of an article whose final and definitive form has been published in the International Journal of Systems Science, 2013, copyright Taylor & Francis; International Journal of Systems Science is available online at: http://www.informaworld.com/ with the DOI: 10.1080/00207721.2013.775386

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