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Robust nonlinear generalised predictive control for a class of uncertain nonlinear systems via an integral sliding mode approach

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journal contribution
posted on 12.04.2016, 14:04 authored by Rachid Errouissi, Jun Yang, Wen-Hua ChenWen-Hua Chen, Ahmed Al-Durra
In this paper, a robust nonlinear generalised predictive control (GPC) method is proposed by combining an integral sliding mode approach. The composite controller can guarantee zero steady-state error for a class of uncertain nonlinear systems in the presence of both matched and unmatched disturbances. Indeed, it is well known that the traditional GPC based on Taylor series expansion cannot completely reject unknown disturbance and achieve offset-free tracking performance. To deal with this problem, the existing approaches are enhanced by avoiding the use of the disturbance observer and modifying the gain function of the nonlinear integral sliding surface. This modified strategy appears to be more capable of achieving both the disturbance rejection and the nominal prescribed specifications for matched disturbance. Simulation results demonstrate the effectiveness of the proposed approach.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

International Journal of Control

Pages

1 - 13

Citation

ERROUISSI, R. ... et al., 2016. Robust nonlinear generalised predictive control for a class of uncertain nonlinear systems via an integral sliding mode approach. International Journal of Control, 89(8), pp. 1698-1710.

Publisher

© Taylor & Francis

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2016-02-15

Notes

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Control on 15/02/2016, available online: http://dx.doi.org/10.1080/00207179.2016.1145356.

ISSN

0020-7179

eISSN

1366-5820

Language

en