Brief A probabilistically constrained model predictive controller

Authors:
Pu Li;Moritz Wendt;GüNter Wozny
Affiliations:
Institut für Prozeí- und Anlagentechnik, Technische Universität Berlin, 10623 Berlin, Germany;Institut für Prozeí- und Anlagentechnik, Technische Universität Berlin, 10623 Berlin, Germany;Institut für Prozeí- und Anlagentechnik, Technische Universität Berlin, 10623 Berlin, Germany
Venue:
Automatica (Journal of IFAC)
Year:
2002

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Abstract

We propose a novel control algorithm, probabilistically constrained predictive control, to deal with the uncertainties of system disturbances. The output is to be controlled in the constrained range with a desired probability. Under the assumption of a linear system, the formulated joint probabilistically constrained problem is convex. Thus, it can be solved with a nonlinear programming solver. The probabilities and gradients of the constraints, composed of disturbance sequences with multivariate normal distribution, are computed using an efficient simulation approach. The results of a test problem show the effectiveness of the proposed algorithm.