Robust model predictive control of uncertain linear systems with persistent disturbances and input constraints

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publication2013 European Control Conference, ECC 2013
Pages542-547
Publication statusPublished - 2013

Conference

Title2013 12th European Control Conference, ECC 2013
PlaceSwitzerland
CityZurich
Period17 - 19 July 2013

Abstract

This paper presents computationally attractive robust model predictive control approaches for the control of discrete-time linear systems with input constraints, structured parameter uncertainties and persistent disturbances. In order to ensure robust stability of constrained uncertain systems, constructive methods are proposed to compute robust positively invariant sets for stabilizing predictive controller. The proposed robust predictive control (RMPC) systems satisfy both recursive feasibility and input-to-state stability. In the controller design, the 0-step predictive controller with a simple structure is proposed. In order to deal with the RMPC problem with a fixed terminal set, the result is extended to the N-step predictive controller. Simulations results have demonstrated the efficacy of the proposed predictive control approaches. © 2013 EUCA.

Citation Format(s)

Robust model predictive control of uncertain linear systems with persistent disturbances and input constraints. / Yang, Weilin; Feng, Gang; Zhang, Tiejun.
2013 European Control Conference, ECC 2013. 2013. p. 542-547 6669673.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review