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Robust Parameter-Dependent Constrained Model Predictive Control

Xia, Yuanqing, Cheng, Jie, Shi, Peng and Liu, Guo-Ping (2007) Robust Parameter-Dependent Constrained Model Predictive Control. In: Second International Conference on Innovative Computing, Information and Control, 2007. ICICIC '07. IEEE, New York, N.Y., pp. 521-524.

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The problem of robust constrained model predictive control (MFC) of systems with polytopic uncertainty is considered in this paper. New sufficient conditions for the existence of parameter-dependent Lyapunov functions are proposed in terms of linear matrix inequalities (LMIs), which will reduce the conservativeness resulting from using a single Lyapunov function. At each sampling instant, the corresponding parameter-dependent Lyapunov function is an upper bound for a worst-case objective function, which can be minimized using the LMI convex optimization approach. Based on the solution of optimization at each sampling instant, the corresponding state feedback controller is designed, which can guarantee that the resulting closed-loop system is robustly asymptotically stable. In addition, the feedback controller will meet the specifications for systems with input or output constraints, for all admissible time-varying parameter uncertainties. Numerical examples are presented to demonstrate the effectiveness of the proposed techniques.

Item Type: Book Section
ISBN: 0769528821, 9780769528823
Uncontrolled Keywords: ResPubID18957, Lyapunov methods, asymptotic stability, control system synthesis, linear matrix inequalities, predictive control, robust control, state feedback, uncertain systems
Subjects: Current > FOR Classification > 0102 Applied Mathematics
Current > FOR Classification > 0906 Electrical and Electronic Engineering
Historical > Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM)
Depositing User: VUIR
Date Deposited: 18 Jan 2014 08:39
Last Modified: 19 Mar 2015 05:16
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Citations in Scopus: 1 - View on Scopus

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