A tractable approximation of chance constrained stochastic MPC based on affine disturbance feedback

• Published in: 2008 47th IEEE Conference on Decision and Control pp. 4731 - 4736
• Main Authors: Oldewurtel, F., Jones, C.N., Morari, M.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2008
• Subjects: Automatic control; Control systems; Linear feedback control systems; Open loop systems; Predictive control; Predictive models; Robustness; State feedback; Stochastic processes; Stochastic systems
• ISBN: 9781424431236; 1424431239
• ISSN: 0191-2216
• DOI: 10.1109/CDC.2008.4738806

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.