Model Reduction of Markovian Jump Systems With Uncertain Probabilities
- Authors
- Shen, Ying; Wu, Zheng-Guang; Shi, Peng; Ahn, Choon Ki
- Issue Date
- 1월-2020
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Asynchronization; hidden Markov model; model reduction; nonhomogeneous Markovian chain; partially unknown conditional probabilities
- Citation
- IEEE TRANSACTIONS ON AUTOMATIC CONTROL, v.65, no.1, pp.382 - 388
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON AUTOMATIC CONTROL
- Volume
- 65
- Number
- 1
- Start Page
- 382
- End Page
- 388
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/58552
- DOI
- 10.1109/TAC.2019.2915827
- ISSN
- 0018-9286
- Abstract
- This paper studies the problem of model reduction for nonhomogeneous Markovian jump systems. The transition probability matrix of the nonhomogeneous Markovian chain has the characteristic of a polytopic structure. An asynchronous reduced-order model is considered, and the asynchronization is modeled by a hidden Markov model with a partially unknown conditional probability matrix. Under this framework, a new sufficient condition is proposed to ensure that the augmented system is stochastically mean-square stable with a specified level of $H_\infty$ performance. Finally, a numerical example is provided to show the effectiveness and advantages of the theoretic results obtained.
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