Publication: Robust MPC based on polyhedral invariant sets for LPV systems
Issued Date
2013-01-01
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14746670
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2-s2.0-84896332877
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Mahidol University
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SCOPUS
Bibliographic Citation
IFAC Proceedings Volumes (IFAC-PapersOnline). Vol.10, No.PART 1 (2013), 355-360
Suggested Citation
Soorathep Kheawhom, Pornchai Bumroongsri Robust MPC based on polyhedral invariant sets for LPV systems. IFAC Proceedings Volumes (IFAC-PapersOnline). Vol.10, No.PART 1 (2013), 355-360. doi:10.3182/20131218-3-IN-2045.00129 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/31775
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Title
Robust MPC based on polyhedral invariant sets for LPV systems
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Abstract
A robust model predictive control (RMPC) using polyhedral invariant sets for linear parameter varying (LPV) systems is presented in this work. A sequence of state feedback gains associated with a sequence of nested polyhedral invariant sets is constructed off-line in order to reduce the computational burdens. At each control iteration, when the measured state lies between any two adjacent polyhedral invariant sets constructed, a state feedback gain is determined by interpolation of two pre-computed state feedback gains incorporated with scheduling parameters. Three interpolation algorithms are proposed. In the first algorithm, the real-time state feedback gain is determined by maximizing the state feedback gain with subjected to a set of constraints associated with current invariant set. In the second algorithm, the real-time state feedback gain is calculated by minimizing the violation of the constraints of the adjacent inner invariant set with subjected to a set of constraints associated with current invariant set. In the last algorithm, the real-time state feedback gain is obtaned by minimizing the upper bound of infinite horizon worst case performance cost, which is estimated by Lyapunov function at current state, with subjected to a set of constraints associated with current invariant set. The controller design is illustrated with a case study of nonlinear two-tank system. The simulation results showed that the proposed RMPC with interpolation provides a better control performance while on-line computation is still tractable as compared to previously reported algorithms. © IFAC.