Robust model predictive control for constrained linear systems based on contractive set and multi-parameter linear programming

A new robust model predictive control (MPC) approach is proposed for constrained linear systems in this paper. It adopts a contractive state set as terminal set in MPC problem and employs a novel function of the state with respect to this terminal set as the stage cost of the objective function. Whe...

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Veröffentlicht in:SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483) Jg. 4; S. 3073 - 3078 vol.4
Hauptverfasser: Sheng Yunlong, Liu Bin, Su Hongye, Chu Jian
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 2003
Schlagworte:
Control systems
Cost function
Linear feedback control systems
Linear programming
Linear systems
Predictive control
Predictive models
Robust control
Robust stability
State feedback
ISBN:9780780379527, 0780379527
ISSN:1062-922X
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Zusammenfassung:A new robust model predictive control (MPC) approach is proposed for constrained linear systems in this paper. It adopts a contractive state set as terminal set in MPC problem and employs a novel function of the state with respect to this terminal set as the stage cost of the objective function. When the controlled systems are subject to linear constraints, explicit MPC law can be obtained as a piecewise affine linear state feedback control law via multi-parameter linear programming method. The presented MPC, along with linear variable-structure control law associated with the terminal set, is essentially a dual mode control scheme to stabilize the constrained uncertain linear system. Compared to the existing MPC methods, the proposed approach have both better real-time applicability and more general robust stability guarantee.
ISBN:9780780379527
0780379527
ISSN:1062-922X
DOI:10.1109/ICSMC.2003.1244362