4.7 Article

Observer-based asynchronous feedback H∞ control for delayed fuzzy implicit jump systems under HMM and event-trigger mechanisms

Journal

INFORMATION SCIENCES
Volume 631, Issue -, Pages 45-64

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2023.02.040

Keywords

Event-driven strategy; Observer-based asynchronous control; Hidden Markovian model; Free weight matrix method; Exponential decrease triggering function

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This paper investigates the observer-based asynchronous feedback H-infinity control problem for time-varying delay fuzzy implicit jump systems under event-driven strategy. A hidden Markovian model is used to capture the asynchronization mechanism between the modes of controlled system and the modes of controller. By applying free weight matrix method and singular value decomposition technique, new observer-based asynchronous H-infinity control criteria are obtained to guarantee that the delayed fuzzy implicit jump systems satisfy stochastic admissibility with H-infinity performance. The effectiveness and practicality of the results are verified through simulation examples including a practical system of single-link robot arm.
This paper investigates the observer-based asynchronous feedback H-infinity control problem for time-varying delay fuzzy implicit jump systems under event-driven strategy. A hidden Markovian model is used to capture the asynchronization mechanism between the modes of controlled system and the modes of controller. By applying free weight matrix method and singular value decomposition technique, new observer-based asynchronous H-infinity control criteria are obtained to guarantee that the delayed fuzzy implicit jump systems satisfy stochastic admissibility with H-infinity performance. The observer-based event-driven asynchronous fuzzy controller is designed by utilizing parallel distributed compensation technique, event-triggering strategy and hidden Markovian model mechanism. In this case, a triggering function characterized with exponential decreasing is adopted to derive the driving threshold that decides when the data needs to be transferred. Simulation examples including a practical system of single-link robot arm are utilized to verify the effectiveness and practicality of the results.

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