On control of discrete-time state-dependent jump linear systems with probabilistic constraints: A receding horizon approach

被引：19

作者：

Chitraganti, Shaikshavali ^{[1
]}

Aberkane, Samir ^{[1
]}

Aubrun, Christophe ^{[1
]}

Valencia-Palomo, Guillermo ^{[2
]}

Dragan, Vasile ^{[3
]}

机构：

[1] Univ Lorraine, CRAN CNRS UMR 7039, F-54500 Vandoeuvre Les Nancy, France

[2] Inst Tecnol Hermosillo, Mexico City 83170, DF, Mexico

[3] Romanian Acad, Inst Math Simon Stoilow, Bucharest, Romania

来源：

SYSTEMS & CONTROL LETTERS | 2014年 / 74卷

关键词：

Jump linear systems; Stochastic model predictive control; Probabilistic state constraints; Linear state-feedback; Second moment stability; MODEL-PREDICTIVE CONTROL; STOCHASTIC STABILITY; FEEDBACK-CONTROL; SUBJECT;

D O I：

10.1016/j.sysconle.2014.10.008

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this article, we consider a receding horizon control of discrete-time state-dependent jump linear systems, a particular kind of stochastic switching systems, subject to possibly unbounded random disturbances and probabilistic state constraints. Due to the nature of the dynamical system and the constraints, we consider a one-step receding horizon. Using inverse cumulative distribution function, we convert the probabilistic state constraints to deterministic constraints, and obtain a tractable deterministic receding horizon control problem. We consider the receding horizon control law to have a linear state-feedback and an admissible offset term. We ensure mean square boundedness of the state variable via solving linear matrix inequalities off-line, and solve the receding horizon control problem online with control offset terms. We illustrate the overall approach applied on a macroeconomic system. (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：81 / 89

页数：9

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