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A Tractable Approximation of Chance Constrained Stochastic MPC based on Affine Disturbance Feedback

Author(s):

F. Oldewurtel
Conference/Journal:

Conference on Decision and Control (CDC), Cancun, Mexico
Abstract:

This paper deals with model predictive control of uncertain linear discrete-time systems with polytopic constraints on the input and chance constraints on the states. When having polytopic constraints and bounded disturbances, the robust problem with an open-loop prediction formulation is known to be conservative. Recently, a tractable closed-loop prediction formulation was introduced, which can reduce the conservatism of the robust problem. We show that in the presence of chance constraints and stochastic disturbances, this closed-loop formulation can be used together with a tractable approximation of the chance constraints to further increase the performance while satisfying the chance constraints with the predefined probability.

Year:

2008
Type of Publication:

(06)Talk
Supervisor:



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