Adaptive dynamic programming‐based decentralized event‐triggered control of large‐scale nonlinear systems
This paper proposes an adaptive dynamic programming (ADP)‐based decentralized event‐triggered control strategy for large‐scale nonlinear systems with event‐triggered scheme to efficiently reduce communication cost and computational burden. Under the event‐triggered mechanism, an local neural network...
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| Published in: | Asian journal of control Vol. 24; no. 4; pp. 1542 - 1556 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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01.07.2022
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| ISSN: | 1561-8625, 1934-6093 |
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| Abstract | This paper proposes an adaptive dynamic programming (ADP)‐based decentralized event‐triggered control strategy for large‐scale nonlinear systems with event‐triggered scheme to efficiently reduce communication cost and computational burden. Under the event‐triggered mechanism, an local neural networks (NNs)‐based observer is introduced to identify the mismatched interconnections and the estimation error is guaranteed to be uniformly ultimately bounded (UUB). Then, a decentralized triggering condition related to the approximation error of interconnections is designed to reduce the local controller updates with guaranteed overall stabilization of large‐scale systems. By virtue of critic‐only structure, the local optimal control policy can be approximated via aperiodic tuning rule using ADP. In addition, the closed‐loop large‐scale system ensures to be asymptotically stable with adaptive triggering threshold according to Lyapunov method. Finally, the simulation results justify the theoretical analysis and illustrate the effectiveness of the proposed event‐triggered control (ETC) strategy. |
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| AbstractList | This paper proposes an adaptive dynamic programming (ADP)‐based decentralized event‐triggered control strategy for large‐scale nonlinear systems with event‐triggered scheme to efficiently reduce communication cost and computational burden. Under the event‐triggered mechanism, an local neural networks (NNs)‐based observer is introduced to identify the mismatched interconnections and the estimation error is guaranteed to be uniformly ultimately bounded (UUB). Then, a decentralized triggering condition related to the approximation error of interconnections is designed to reduce the local controller updates with guaranteed overall stabilization of large‐scale systems. By virtue of critic‐only structure, the local optimal control policy can be approximated via aperiodic tuning rule using ADP. In addition, the closed‐loop large‐scale system ensures to be asymptotically stable with adaptive triggering threshold according to Lyapunov method. Finally, the simulation results justify the theoretical analysis and illustrate the effectiveness of the proposed event‐triggered control (ETC) strategy. |
| Author | Li, Shaoyuan Zou, Yuanyuan Hu, Chuanhao |
| Author_xml | – sequence: 1 givenname: Chuanhao surname: Hu fullname: Hu, Chuanhao organization: Shanghai Jiao Tong University – sequence: 2 givenname: Yuanyuan orcidid: 0000-0002-8995-020X surname: Zou fullname: Zou, Yuanyuan email: yuanyzou@sjtu.edu.cn organization: Shanghai Jiao Tong University – sequence: 3 givenname: Shaoyuan orcidid: 0000-0001-9488-9143 surname: Li fullname: Li, Shaoyuan organization: Shanghai Jiao Tong University |
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| Cites_doi | 10.1002/asjc.1443 10.1016/j.ifacol.2019.09.111 10.23919/ACC.2018.8431695 10.1002/asjc.1823 10.1016/0005-1098(88)90013-1 10.1049/iet-cta.2016.1383 10.1109/9.486636 10.1016/j.neucom.2018.09.029 10.1007/s12555-016-0711-5 10.23919/ACC.2019.8814295 10.1109/JAS.2014.7004686 10.1109/TSMCB.2007.904544 10.1016/j.neucom.2016.06.020 10.1002/asjc.1834 10.1002/asjc.1831 10.1016/j.automatica.2008.08.017 10.1109/TSMC.2017.2690665 10.1016/j.automatica.2014.03.015 10.1109/ICCA.2019.8899605 10.1002/asjc.1754 10.1109/TNNLS.2017.2693205 10.1109/TCYB.2019.2946122 10.1109/CDC.2008.4738955 10.1109/TAC.2011.2180089 10.1109/TSMC.2019.2898370 10.1109/IJCNN.2016.7727753 10.1109/TNNLS.2013.2280013 10.1109/TSMC.2018.2852810 10.1109/IJCNN.2014.6889787 10.1109/TNNLS.2016.2614002 10.1016/j.automatica.2018.10.019 10.1016/j.neucom.2015.08.119 10.1002/asjc.2147 |
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| SubjectTerms | Adaptive control adaptive dynamic programming Approximation critic NNs Dynamic programming Event triggered control event‐triggered Interconnections Neural networks NN‐based observer Nonlinear systems Optimal control |
| Title | Adaptive dynamic programming‐based decentralized event‐triggered control of large‐scale nonlinear systems |
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