제어로봇시스템학회:학술대회논문집
- 2004.08a
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- Pages.530-535
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- 2004
State set estimation based MPC for LPV systems with input constraint
- Jeong, Seung-Cheol (Electrical and Computer Engineering Division, Pohang University of Science and Technology) ;
- Kim, Sung-Hyun (Electrical and Computer Engineering Division, Pohang University of Science and Technology) ;
- Park, Poo-Gyeon (Electrical and Computer Engineering Division, Pohang University of Science and Technology)
- Published : 2004.08.25
Abstract
This paper considers a state set estimation (SSE) based model predictive control (MPC) for linear parameter- varying (LPV) systems with input constraint. We estimate, at each time instant, a feasible set of all states which are consistent with system model, measurements and a priori information, rather than the state itself. By combining a state-feedback MPC and an SSE, we design an SSE-based MPC algorithm that stabilizes the closed-loop system. The proposed algorithm is solved by semi-de�nite program involving linear matrix inequalities. A numerical example is included to illustrate the performance of the proposed algorithm.
Keywords
- receding horizon control;
- state set estimation;
- output feedback control;
- input constraint;
- linear matrix inequality