Robust finite-time H ∞ control for uncertain singular stochastic Markovian jump systems via proportional differential control law
- Author(s): Li Li 1, 2 ; Qingling Zhang 1, 3 ; Jian Li 1 ; Guoliang Wang 4
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View affiliations
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Affiliations:
1:
Institute of Systems Science, Northeastern University, Shenyang, Liaoning 110819, People's Republic of China;
2: College of Mathematics, Physics, Bohai University, Jinzhou, Liaoning 121013, People's Republic of China;
3: State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, Liaoning 110819, People's Republic of China;
4: School of Information and Control Engineering, Liaoning Shihua University, Fushun, Liaoning 113001, People's Republic of China
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Affiliations:
1:
Institute of Systems Science, Northeastern University, Shenyang, Liaoning 110819, People's Republic of China;
- Source:
Volume 8, Issue 16,
06 November 2014,
p.
1625 – 1638
DOI: 10.1049/iet-cta.2014.0194 , Print ISSN 1751-8644, Online ISSN 1751-8652
This study focuses on the problem of robust finite-time H ∞ control for a class of uncertain singular stochastic Markovian jump systems with partially unknown transition rates via proportional differential control law (PDLC). The uncertainties are not only in state matrices and input matrices but also in differential matrices. New sufficient conditions for the existence of mode-dependent PDLC are derived in the form of strict linear matrix inequalities, such that the closed-loop system of the singular stochastic Markovian jump system is not only stochastic finite-time stable but also satisfies a prescribed performance. Numerical examples are used to show the effectiveness of the proposed methods.
Inspec keywords: PD control; H∞ control; robust control; uncertain systems; Markov processes; stochastic systems; linear matrix inequalities
Other keywords: sufficient conditions; differential matrix; mode dependent PDLC; partially unknown transition rate; input matrix; robust finite time H∞ control; uncertain singular stochastic Markovian jump system; linear matrix inequalities; state matrix; proportional differential control law
Subjects: Control system analysis and synthesis methods; Optimal control; Time-varying control systems; Markov processes; Linear algebra (numerical analysis)
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