mathcal Control of Constrained Markov Jump Systems With Intermittent Mode Information Loss

This paper investigates <inline-formula><tex-math notation="LaTeX">\mathcal {H}_\infty</tex-math></inline-formula> control for continuous-time Markov jump systems subject to joint input-state constraint and intermittent mode information loss. The considered constrai...

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Veröffentlicht in:IEEE transactions on automatic control Jg. 68; H. 12; S. 1 - 8
Hauptverfasser: Shen, Ying, Wu, Zheng-Guang, Shi, Peng, Chen, Bo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: IEEE 01.12.2023
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<inline-formula xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"> <tex-math notation="LaTeX"> mathcal {h}_\infty</tex-math> </inline-formula> control
Generators
Hidden Markov models
intermittent mode information loss
joint input-state constraint
Lyapunov methods
markov jump systems
Markov processes
Probability distribution
Safety
State feedback
ISSN:0018-9286, 1558-2523
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Abstract This paper investigates <inline-formula><tex-math notation="LaTeX">\mathcal {H}_\infty</tex-math></inline-formula> control for continuous-time Markov jump systems subject to joint input-state constraint and intermittent mode information loss. The considered constraint, which is defined as a quadratic function of the system state and control input, is very general since it covers the input constraint, state constraint or other constraints for physical quantities of interest. The mode information loss is described by a Bernoulli stochastic process. As a result, the system mode and controller mode form a special case of hidden Markov model. By means of an mode-dependent Lyapunov function, a sufficient condition is presented which can guarantee that the closed-loop system is exponentially mean square stable with a certain <inline-formula><tex-math notation="LaTeX">\mathcal {H}_\infty</tex-math></inline-formula> noise attenuation performance under the joint input-state constraint. Finally, an example is presented to analyze the influence of some important parameters and illustrate the effectiveness of the proposed control scheme.
AbstractList This paper investigates <inline-formula><tex-math notation="LaTeX">\mathcal {H}_\infty</tex-math></inline-formula> control for continuous-time Markov jump systems subject to joint input-state constraint and intermittent mode information loss. The considered constraint, which is defined as a quadratic function of the system state and control input, is very general since it covers the input constraint, state constraint or other constraints for physical quantities of interest. The mode information loss is described by a Bernoulli stochastic process. As a result, the system mode and controller mode form a special case of hidden Markov model. By means of an mode-dependent Lyapunov function, a sufficient condition is presented which can guarantee that the closed-loop system is exponentially mean square stable with a certain <inline-formula><tex-math notation="LaTeX">\mathcal {H}_\infty</tex-math></inline-formula> noise attenuation performance under the joint input-state constraint. Finally, an example is presented to analyze the influence of some important parameters and illustrate the effectiveness of the proposed control scheme.
Author Shi, Peng
Shen, Ying
Wu, Zheng-Guang
Chen, Bo
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crossref_primary_10_1016_j_jfranklin_2025_107740
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Generators
Hidden Markov models
intermittent mode information loss
joint input-state constraint
Lyapunov methods
markov jump systems
Markov processes
Probability distribution
Safety
State feedback
Title mathcal Control of Constrained Markov Jump Systems With Intermittent Mode Information Loss
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