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Robust Input Covariance Constraint Control for Uncertain Polytopic Systems
Author(s) -
AlJiboory Ali Khudhair,
Zhu Guoming
Publication year - 2016
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.1211
Subject(s) - control theory (sociology) , robust control , covariance , linear matrix inequality , constraint (computer aided design) , convex optimization , mathematical optimization , controller (irrigation) , lyapunov function , mathematics , optimization problem , regular polygon , control (management) , computer science , control system , engineering , nonlinear system , artificial intelligence , agronomy , physics , quantum mechanics , biology , statistics , geometry , electrical engineering
Abstract In this paper, the robust input covariance constraint (ICC) control problem with polytopic uncertainty is solved using convex optimization with linear matrix inequality (LMI) approach. The ICC control problem is an optimal control problem that optimizes the output performance subjected to multiple constraints on the input covariance matrices. This control problem has significant practical implications when hard constraints need to be satisfied on control actuators. The contribution of this paper is the characterization of the control synthesis LMIs used to solve the robust ICC control problem for polytopic uncertain systems. Both continuous‐ and discrete‐time systems are considered. Parameter‐dependent and independent Lyapunov functions have been used for robust ICC controller synthesis. Numerical design examples are presented to illustrate the effectiveness of the proposed approach.