期刊
PROCESSES
卷 10, 期 4, 页码 -出版社
MDPI
DOI: 10.3390/pr10040769
关键词
event-triggered scheduling; Markov jump nonlinear systems(MJNSs); error threshold; partly unknown probabilities; asynchronous filtering
资金
- National Natural Science Foundation of China [61603133]
- Zhejiang Provincial Public Welfare Technology Application Research Project of China [LGG21E020001, LGG22F030023]
This paper focuses on the problem of event-triggered H-infinity asynchronous filtering for Markov jump nonlinear systems with varying delay and unknown probabilities. An event-triggered scheduling scheme is adopted to decrease the transmission rate of measured outputs. The designed filter is mode dependent and asynchronous with the original system, which is represented by a hidden Markov model (HMM). Under this framework, a sufficient condition is given and the filter is further devised to ensure the resulting filtering error dynamic system is stochastically stable with a desired H-infinity disturbance attenuation performance.
This paper focuses on the problem of event-triggered H-infinity asynchronous filtering for Markov jump nonlinear systems with varying delay and unknown probabilities. An event-triggered scheduling scheme is adopted to decrease the transmission rate of measured outputs. The devised filter is mode dependent and asynchronous with the original system, which is represented by a hidden Markov model (HMM). Both the probability information involved in the original system and the filter are assumed to be only partly available. Under this framework, via employing the Lyapunov-Krasovskii functional and matrix inequality transformation techniques, a sufficient condition is given and the filter is further devised to ensure that the resulting filtering error dynamic system is stochastically stable with a desired H-infinity, disturbance attenuation performance. Lastly, the validity of the presented filter design scheme is verified through a numerical example.
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