Fuzzy-model-based robust control of Markov jump nonlinear systems with incomplete transition probabilities and uncertain packet dropouts
Interval type-2 fuzzy Markov jump systems (IT2FMJSs) have received much attention because they can well describe complex nonlinear systems with uncertainties and stochastic system mode switching. However, the transition probabilities of fuzzy MJSs (FMJSs) have been assumed to be completely known, li...
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sg-ntu-dr.10356-1712292023-10-17T07:03:24Z Fuzzy-model-based robust control of Markov jump nonlinear systems with incomplete transition probabilities and uncertain packet dropouts Xu, Zeyuan Shi, Shaolong Er, Meng Joo Hu, Zhijian School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Incomplete Transition Probabilities Markov Jump Systems Interval type-2 fuzzy Markov jump systems (IT2FMJSs) have received much attention because they can well describe complex nonlinear systems with uncertainties and stochastic system mode switching. However, the transition probabilities of fuzzy MJSs (FMJSs) have been assumed to be completely known, limiting real-world applications of existing results. Different from the previous studies, transition probabilities between system modes switching are partially unknown, and packet dropouts of data transmission are uncertain in this study. Compared with the previous studies, the main advantages of this work are as follows: (1) To analyze stochastic stability and reduce conservatism of existing approaches, a novel Lyapunov function that depends on both system mode and fuzzy basis function is constructed; (2) the existence of a mode-dependent and fuzzy-basis-dependent state feedback controller is revealed; (3) stochastic stability of closed-loop system with a desired (Formula presented.) performance is established, and the problem of incomplete transition probabilities and uncertain packet dropouts has been completely addressed. An illustrative example of a robot arm is used to demonstrate the effectiveness and practicality of the proposed control strategy. By virtue of the proposed strategy, the effects of incomplete transition probabilities and uncertain packet dropouts on IT2FMJSs have been completely alleviated. This work was funded by: Dalian Maritime University Research Fund for Central Universities, Grant/Award Number: 3132019344; Division of Science and Technology Grant, Grant/Award Number: 017212213; Hong Kong Scholars Program, Grant/Award Number: XJ2021007; National Natural Science Foundation of China, Grant/Award Number: 62102071; Natural Science Foundation of Sichuan Province, Grant/Award Number: 2022NSFSC0873; Research Foundation of Artificial Intelligence Key Laboratory of Sichuan Province, Grant/Award Number: 2021RYJ05 2023-10-17T07:03:24Z 2023-10-17T07:03:24Z 2023 Journal Article Xu, Z., Shi, S., Er, M. J. & Hu, Z. (2023). Fuzzy-model-based robust control of Markov jump nonlinear systems with incomplete transition probabilities and uncertain packet dropouts. Asian Journal of Control. https://dx.doi.org/10.1002/asjc.3188 1561-8625 https://hdl.handle.net/10356/171229 10.1002/asjc.3188 2-s2.0-85165247997 en Asian Journal of Control © 2023 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd. All rights reserved. |
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Engineering::Electrical and electronic engineering Incomplete Transition Probabilities Markov Jump Systems Xu, Zeyuan Shi, Shaolong Er, Meng Joo Hu, Zhijian Fuzzy-model-based robust control of Markov jump nonlinear systems with incomplete transition probabilities and uncertain packet dropouts |
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Interval type-2 fuzzy Markov jump systems (IT2FMJSs) have received much attention because they can well describe complex nonlinear systems with uncertainties and stochastic system mode switching. However, the transition probabilities of fuzzy MJSs (FMJSs) have been assumed to be completely known, limiting real-world applications of existing results. Different from the previous studies, transition probabilities between system modes switching are partially unknown, and packet dropouts of data transmission are uncertain in this study. Compared with the previous studies, the main advantages of this work are as follows: (1) To analyze stochastic stability and reduce conservatism of existing approaches, a novel Lyapunov function that depends on both system mode and fuzzy basis function is constructed; (2) the existence of a mode-dependent and fuzzy-basis-dependent state feedback controller is revealed; (3) stochastic stability of closed-loop system with a desired (Formula presented.) performance is established, and the problem of incomplete transition probabilities and uncertain packet dropouts has been completely addressed. An illustrative example of a robot arm is used to demonstrate the effectiveness and practicality of the proposed control strategy. By virtue of the proposed strategy, the effects of incomplete transition probabilities and uncertain packet dropouts on IT2FMJSs have been completely alleviated. |
author2 |
School of Electrical and Electronic Engineering |
author_facet |
School of Electrical and Electronic Engineering Xu, Zeyuan Shi, Shaolong Er, Meng Joo Hu, Zhijian |
format |
Article |
author |
Xu, Zeyuan Shi, Shaolong Er, Meng Joo Hu, Zhijian |
author_sort |
Xu, Zeyuan |
title |
Fuzzy-model-based robust control of Markov jump nonlinear systems with incomplete transition probabilities and uncertain packet dropouts |
title_short |
Fuzzy-model-based robust control of Markov jump nonlinear systems with incomplete transition probabilities and uncertain packet dropouts |
title_full |
Fuzzy-model-based robust control of Markov jump nonlinear systems with incomplete transition probabilities and uncertain packet dropouts |
title_fullStr |
Fuzzy-model-based robust control of Markov jump nonlinear systems with incomplete transition probabilities and uncertain packet dropouts |
title_full_unstemmed |
Fuzzy-model-based robust control of Markov jump nonlinear systems with incomplete transition probabilities and uncertain packet dropouts |
title_sort |
fuzzy-model-based robust control of markov jump nonlinear systems with incomplete transition probabilities and uncertain packet dropouts |
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2023 |
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https://hdl.handle.net/10356/171229 |
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1781793761421950976 |