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Robust output‐based controller design for enlarging the region of attraction of input saturated linear systems
Author(s) -
Mera Manuel,
Salgado Iván,
Chairez Isaac
Publication year - 2021
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.2181
Subject(s) - control theory (sociology) , ellipsoid , bounded function , convex optimization , lyapunov function , mathematics , state observer , saturation (graph theory) , observer (physics) , convergence (economics) , linear system , robust control , controller (irrigation) , linear matrix inequality , regular polygon , mathematical optimization , control system , nonlinear system , computer science , control (management) , engineering , mathematical analysis , physics , biology , artificial intelligence , economic growth , geometry , quantum mechanics , agronomy , astronomy , combinatorics , electrical engineering , economics
The aim of this study was to design a constrained robust output feedback control strategy for stabilizing linear systems affected by uncertainties and output perturbations. The input is constrained by a saturation function. A classical Luenberger observer reconstructed the states from output observations. The state feedback control employed the estimated states given by the observer. This work proposed a Barrier Lyapunov Function (BLF) to manage the saturation problem in the control input. Moreover, an extended version of the attractive ellipsoid method (AEM) characterized the zone of convergence due the presence of perturbations in the output. A convex optimization procedure, formulated as a set of matrix inequalities, yielded the control parameters and the region of attraction for the close‐loop system as well as a minimal ultimately bounded set for the system trajectories. Numerical simulations supported the theoretical results formulated in this study.