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Optimizing the performance of the feedback controller for state‐based switching bilinear systems
Author(s) -
Lin Shu,
Li Dewei,
Schutter Bart
Publication year - 2020
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2639
Subject(s) - control theory (sociology) , bilinear interpolation , upper and lower bounds , lyapunov function , mathematics , controller (irrigation) , state (computer science) , optimization problem , stability (learning theory) , mathematical optimization , computer science , control (management) , nonlinear system , algorithm , artificial intelligence , agronomy , biology , mathematical analysis , statistics , physics , quantum mechanics , machine learning
Summary This article is concerned with the design and performance optimization of feedback controllers for state‐based switching bilinear systems (SBLSs), where subsystems take the form of bilinear systems in different state space polyhedra. First, by further dividing the subregions into smaller regions and designing region‐dependent feedback controllers in the resulting regions, the SBLSs can be transformed into corresponding switching linear systems (SLSs). Then, for these SLSs, by imposing contractility conditions on the Lyapunov functions, an upper bound on the infinite horizon quadratic cost can be obtained. Optimizing this upper bound yields the controller design. The optimization problem is formulated as a linear matrix inequalities optimization problem, which can be solved efficiently. Finally, the stability of the close‐loop system under the proposed controller is established step by step through a decreasing overall Lyapunov function.