Robust dynamic programming for min-max model predictive control of constrained uncertain systems
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. ISSN 0018-9286Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/TAC.2004.838489
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|
|Subjects:||T Technology > TL Motor vehicles. Aeronautics. Astronautics
T Technology > TK Electrical engineering. Electronics Nuclear engineering
|Journal or Publication Title:||IEEE TRANSACTIONS ON AUTOMATIC CONTROL|
|Publisher:||IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC|
|Number of Pages:||5|
|Page Range:||pp. 2253-2257|
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