Output feedback model predictive control for LPV systems based on quasi-min-max algorithm

Authors:
Jee-Hun Park;Tae-Hyoung Kim;Toshiharu Sugie
Affiliations:
Department of Systems Science, Kyoto University, Uji, Kyoto 611-0011, Japan;School of Mechanical Engineering, Chung-Ang University, 221 Heukseok-dong, Dongjak-gu, Seoul 156-756, Republic of Korea;Department of Systems Science, Kyoto University, Uji, Kyoto 611-0011, Japan
Venue:
Automatica (Journal of IFAC)
Year:
2011

Citing 8
Cited 1

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Worst-case formulations of model predictive control for systems with bounded parameters

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Survey Constrained model predictive control: Stability and optimality

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Quasi-Min-Max MPC algorithms for LPV systems

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Brief An improved approach for constrained robust model predictive control

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Technical Communique: Min-max predictive control strategies for input-saturated polytopic uncertain systems

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Brief An efficient off-line formulation of robust model predictive control using linear matrix inequalities

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Correspondence: Robust stabilization of uncertain time-varying discrete systems and comments on "an improved approach for constrained robust model predictive control"

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Correspondence: Comments on "Output feedback model predictive control for LPV systems based on quasi-min-max algorithm"

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Abstract

This paper proposes a robust output feedback model predictive control (MPC) scheme for linear parameter varying (LPV) systems based on a quasi-min-max algorithm. This approach involves an off-line design of a robust state observer for LPV systems using linear matrix inequality (LMI) and an on-line robust output feedback MPC algorithm using the estimated state. The proposed MPC method for LPV systems is applicable for a variety of systems with constraints and guarantees the robust stability of the output feedback systems. A numerical example for an LPV system subject to input constraints is given to demonstrate its effectiveness.