Discrete‐Time Uncertain Event‐Triggered H∞ Control for Slow Sampling Markov Jump Systems With Strictly Dissipativity

ABSTRACT This paper investigates the H∞$$ {H}_{\infty } $$ control problem for discrete‐time uncertain slow sampling Markov jump systems under the event‐triggered scheme. Discrete‐time Markov jumps are controlled using an event‐triggered scheme. An event‐based strategy is addressed to reduce the dat...

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Vydáno v:	Mathematical methods in the applied sciences Ročník 48; číslo 11; s. 10896 - 10908
Hlavní autoři:	Kchaou, Mourad, Syed Ali, M., Vigneshwar, B., Sanober, Sumaya, Ibrahim, Tarek F., D Alanazi, Faizah
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Freiburg Wiley Subscription Services, Inc 30.07.2025
Témata:	Control theory Dissipation dissipative H∞$$ {H}_{\infty } $$ control Feedback control H-infinity control Linear matrix inequalities Markov jump systems Parameter uncertainty Sampling State feedback uncertainties
ISSN:	0170-4214, 1099-1476
On-line přístup:	Získat plný text
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Shrnutí:	ABSTRACT This paper investigates the H∞$$ {H}_{\infty } $$ control problem for discrete‐time uncertain slow sampling Markov jump systems under the event‐triggered scheme. Discrete‐time Markov jumps are controlled using an event‐triggered scheme. An event‐based strategy is addressed to reduce the data communication and improve the control efficiency. By applying a switched Lyapunov functional and linear matrix inequalities (LMIs), we derive sufficient conditions for (Q,S,R)−γ$$ \left(Q,S,R\right)-\gamma $$‐dissipativity of the resulting system. An event‐triggered scheme is introduced into LMIs approaches in order to solve the dissipative control problem. The control strategy is implemented by combining the disturbance output with state feedback control law in order to achieve asymptotically stable closed‐loop systems. Convex combination approach is utilized to handle slow sampling input, while parameter uncertainty and external disturbances are both included, and the robustness H∞$$ {H}_{\infty } $$ performance is analyzed. The developed methods are illustrated with two examples that illustrate their flexibility and applicability.
Bibliografie:	Funding The authors extend their appreciation to the Deanship of Scientific Research at Northern Border University, Arar, KSA, for funding this research work through the project number “NBU‐FFR‐2025‐1102‐05”. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	0170-4214 1099-1476
DOI:	10.1002/mma.10928