A probabilistically constrained model predictive controller

被引：119

作者：

Li, P ^{[1
]}

Wendt, M ^{[1
]}

Wozny, G ^{[1
]}

机构：

[1] Tech Univ Berlin, Inst Prozess & Anlagentech, D-10623 Berlin, Germany

来源：

AUTOMATICA | 2002年 / 38卷 / 07期

关键词：

uncertainty; multivariate normal distribution; probabilistic constraints; predictive control; nonlinear programming;

D O I：

10.1016/S0005-1098(02)00002-X

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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. (C) 2002 Elsevier Science Ltd. All rights reserved.

引用

页码：1171 / 1176

页数：6

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