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Constrained multivariable stable predictive control based on Toeplitz equation
Author(s) -
Liu Bin,
Su Hongye,
Jiang Zheng,
Fang Kangling
Publication year - 2010
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.245
Subject(s) - multivariable calculus , toeplitz matrix , model predictive control , control theory (sociology) , mathematics , controller (irrigation) , transformation (genetics) , linear matrix inequality , factorization , matrix (chemical analysis) , stability (learning theory) , mathematical optimization , computer science , control (management) , algorithm , engineering , control engineering , artificial intelligence , agronomy , biochemistry , chemistry , materials science , gene , pure mathematics , composite material , biology , machine learning
A stable constrained multivariable predictive control algorithm based on the Toeplitz predictive equation is presented. An analytical method for transformation between left and right coprime factorization of multivariable system is put forward, and then an unconstrained control law and its stable condition are given. Furthermore, for the constrained multivariable controlled system, a predictive controller and its asymptotically stable condition are presented and proved. Finally, the constrained receding horizon optimization is transformed into a typical linear matrix inequality (LMI) problem and solved. The detailed control algorithm is depicted in a numerical example, and the simulation results reveal the effectiveness and practicability of the presented algorithm. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society