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Robust dynamic programming for min-max model predictive control of constrained uncertain systems
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UNSPECIFIED (2004) Robust dynamic programming for min-max model predictive control of constrained uncertain systems. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 49 (12). pp. 2253-2257. doi:10.1109/TAC.2004.838489 ISSN 0018-9286.
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Official URL: http://dx.doi.org/10.1109/TAC.2004.838489
Abstract
We address min-max model predictive control (MPC) for uncertain discrete-time systems by a robust dynamic programming approach, and develop an algorithm that is suitable for linearly cons trained polytopic systems with piecewise affine cost functions. The method uses polyhedral representations of the cost-to-go functions and feasible sets, and performs multiparametric programming by a duality based approach in each recursion step. We show how to apply the method to robust MPC, and give conditions guaranteeing closed loop stability. Finally, we apply the method to a tutorial example, a parking car with uncertain mass.
Item Type: | Journal Article | ||||
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Subjects: | T Technology > TL Motor vehicles. Aeronautics. Astronautics T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Journal or Publication Title: | IEEE TRANSACTIONS ON AUTOMATIC CONTROL | ||||
Publisher: | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | ||||
ISSN: | 0018-9286 | ||||
Official Date: | December 2004 | ||||
Dates: |
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Volume: | 49 | ||||
Number: | 12 | ||||
Number of Pages: | 5 | ||||
Page Range: | pp. 2253-2257 | ||||
DOI: | 10.1109/TAC.2004.838489 | ||||
Publication Status: | Published |
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