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Robust control of linear time‐varying systems with constraints
Author(s) -
Zheng Alex,
Morari Manfred
Publication year - 2000
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/1099-1239(200011)10:13<1063::aid-rnc516>3.0.co;2-z
Subject(s) - linear system , robust control , mathematical optimization , computer science , simple (philosophy) , robustness (evolution) , class (philosophy) , optimization problem , robust optimization , stability (learning theory) , set (abstract data type) , time complexity , linear programming , domain (mathematical analysis) , control theory (sociology) , mathematics , control (management) , control system , algorithm , engineering , mathematical analysis , philosophy , biochemistry , chemistry , electrical engineering , epistemology , artificial intelligence , machine learning , gene , programming language
In this paper, we generalize the robust MPC algorithm proposed by Campo and Morari for control of uncertain linear time‐varying systems, represented by finite impulse response models, with constraints. A necessary and sufficient condition on the set of plants for guaranteeing robust asymptotic stability of the closed‐loop system is stated. Although these results hold for any uncertainty description expressed in the time domain, the on‐line computational complexity of the resulting optimization problem depends on the uncertainty description. For a class of uncertainty descriptions, we show that the optimization problem can be cast as a linear program of moderate size. The algorithm is demonstrated on a simple example. Copyright © 2000 John Wiley & Sons, Ltd.