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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Optimal and Robust Sampled-Data Control of Markov Jump Linear Systems: A Differential LMI Approach

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Author(s):
Gabriel, Gabriela W. [1] ; Goncalves, Tiago R. [1] ; Geromel, Jose C. [1]
Total Authors: 3
Affiliation:
[1] Univ Estadual Campinas, Sch Elect & Comp Engn, BR-13083852 Campinas, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: IEEE Transactions on Automatic Control; v. 63, n. 9, p. 3054-3060, SEP 2018.
Web of Science Citations: 5
Abstract

This paper addresses the problem of designing optimal sampled-data state feedback control for continuous-time Markov jump linear systems. Stability and performance robustness against polytopic uncertainty acting on the system parameters including the transition rate matrix are analyzed. The main goal is to characterize the optimal solution of this class of problems in the context of H-2 and H-infinity performances. The theoretical achievements are based on the direct application of the celebrated Bellman's Principle of Optimality expressed in terms of the dynamic programming equation applied to the time interval corresponding to two successive sampling instants. The design conditions are expressed through differential linear matrix inequalities. Examples are solved for illustration. (AU)

FAPESP's process: 16/08043-9 - Linear differential inequalities: numerical solution and applications
Grantee:Tiago Rocha Gonçalves
Support type: Scholarships in Brazil - Master
FAPESP's process: 16/06343-5 - Unified Theory for Sampled-Data Control of Hybrid Dynamic Systems
Grantee:Gabriela Werner Gabriel
Support type: Scholarships in Brazil - Post-Doctorate