{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T03:23:18Z","timestamp":1775791398875,"version":"3.50.1"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Syst Sci Complex"],"published-print":{"date-parts":[[2024,2]]},"DOI":"10.1007\/s11424-024-3429-0","type":"journal-article","created":{"date-parts":[[2024,2,27]],"date-time":"2024-02-27T04:40:12Z","timestamp":1709008812000},"page":"253-272","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["New Results in Cooperative Adaptive Optimal Output Regulation"],"prefix":"10.1007","volume":"37","author":[{"given":"Yuchen","family":"Dong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weinan","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhong-Ping","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,2,27]]},"reference":[{"issue":"8","key":"3429_CR1","doi-asserted-by":"publisher","first-page":"3592","DOI":"10.1109\/TAC.2019.2949894","volume":"65","author":"G D Khan","year":"2020","unstructured":"Khan G D, Chen Z Y, and Zhu L J, A new approach for event-triggered stabilization and output regulation of nonlinear systems, IEEE Transactions on Automatic Control, 2020, 65(8): 3592\u20133599.","journal-title":"IEEE Transactions on Automatic Control"},{"issue":"5","key":"3429_CR2","doi-asserted-by":"publisher","first-page":"2415","DOI":"10.1109\/TAC.2020.3010772","volume":"66","author":"D Liang","year":"2021","unstructured":"Liang D and Huang J, Robust output regulation of linear systems by event-triggered dynamic output feedback control, IEEE Transactions on Automatic Control, 2021, 66(5): 2415\u20132422.","journal-title":"IEEE Transactions on Automatic Control"},{"key":"3429_CR3","doi-asserted-by":"publisher","first-page":"110366","DOI":"10.1016\/j.automatica.2022.110366","volume":"142","author":"W N Gao","year":"2022","unstructured":"Gao W N, Deng C, Jiang Y, et al., Resilient reinforcement learning and robust output regulation under denial-of-service attacks, Automatica, 2022, 142: 110366.","journal-title":"Automatica"},{"issue":"10","key":"3429_CR4","doi-asserted-by":"publisher","first-page":"5229","DOI":"10.1109\/TNNLS.2021.3069728","volume":"33","author":"W N Gao","year":"2022","unstructured":"Gao W N, Mynuddin M, Wunsch D C, et al., Reinforcement learning-based cooperative optimal output regulation via distributed adaptive internal model, IEEE Transactions on Neural Networks and Learning Systems, 2022, 33(10): 5229\u20135240.","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"3429_CR5","doi-asserted-by":"publisher","unstructured":"Zhang Z, Chen S M, and Zheng Y S, Cooperative output regulation for linear multiagent systems via distributed fixed-time event-triggered control, IEEE Transactions on Neural Networks and Learning Systems, 2022, DOI: https:\/\/doi.org\/10.1109\/TNNLS.2022.3174416.","DOI":"10.1109\/TNNLS.2022.3174416"},{"issue":"4","key":"3429_CR6","doi-asserted-by":"publisher","first-page":"2521","DOI":"10.1109\/TAC.2022.3184388","volume":"68","author":"D Zhang","year":"2023","unstructured":"Zhang D, Deng C, and Feng G, Resilient cooperative output regulation for nonlinear multiagent systems under DoS attacks, IEEE Transactions on Automatic Control, 2023, 68(4): 2521\u20132528.","journal-title":"IEEE Transactions on Automatic Control"},{"issue":"6","key":"3429_CR7","doi-asserted-by":"publisher","first-page":"1336","DOI":"10.1109\/TAC.2009.2015546","volume":"54","author":"J Xiang","year":"2009","unstructured":"Xiang J, Wei W, and Li Y, Synchronized output regulation of networked linear systems, IEEE Transactions on Automatic Control, 2009, 54(6): 1336\u20131341.","journal-title":"IEEE Transactions on Automatic Control"},{"key":"3429_CR8","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1007\/978-981-99-3888-9_3","volume":"1058","author":"Y H Qu","year":"2023","unstructured":"Qu Y H, Wang H Y, and Lin S, Smart grid system cooperative output control method based on distributed compensation algorithm, Proceedings of the 5th International Conference on Clean Energy and Electrical Systems, 2023, 1058: 35\u201347.","journal-title":"Proceedings of the 5th International Conference on Clean Energy and Electrical Systems"},{"issue":"2","key":"3429_CR9","doi-asserted-by":"publisher","first-page":"1166","DOI":"10.1109\/TEC.2022.3221619","volume":"38","author":"X Wang","year":"2023","unstructured":"Wang X, He Y, Gao D W, et al., Cooperative output regulation of large-scale wind turbines for power reserve control, IEEE Transactions on Energy Conversion, 2023, 38(2): 1166\u20131177.","journal-title":"IEEE Transactions on Energy Conversion"},{"key":"3429_CR10","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.automatica.2019.01.013","volume":"103","author":"C Deng","year":"2019","unstructured":"Deng C and Yang G H, Distributed adaptive fault-tolerant control approach to cooperative output regulation for linear multi-agent systems, Automatica, 2019, 103: 62\u201368.","journal-title":"Automatica"},{"issue":"1","key":"3429_CR11","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1109\/TAC.2013.2272133","volume":"59","author":"C Huang","year":"2014","unstructured":"Huang C and Ye X D, Cooperative output regulation of heterogeneous multi-agent systems: An H\u221e criterion, IEEE Transactions on Automatic Control, 2014, 59(1): 267\u2013273.","journal-title":"IEEE Transactions on Automatic Control"},{"key":"3429_CR12","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1016\/j.automatica.2016.01.076","volume":"68","author":"Z K Li","year":"2016","unstructured":"Li Z K, Chen M Z Q, and Ding Z T, Distributed adaptive controllers for cooperative output regulation of heterogeneous agents over directed graphs, Automatica, 2016, 68: 179\u2013183.","journal-title":"Automatica"},{"issue":"3","key":"3429_CR13","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1561\/2600000023","volume":"8","author":"Z P Jiang","year":"2020","unstructured":"Jiang Z P, Bian T, and Gao W N, Learning-based control: A tutorial and some recent results, Foundations and Trends in Systems and Control, 2020, 8(3): 176\u2013284.","journal-title":"Foundations and Trends in Systems and Control"},{"issue":"11","key":"3429_CR14","doi-asserted-by":"publisher","first-page":"5208","DOI":"10.1109\/TNNLS.2020.3027301","volume":"32","author":"F Y Zhao","year":"2021","unstructured":"Zhao F Y, Gao W N, Jiang Z P, et al., Event-triggered adaptive optimal control with output feedback: An adaptive dynamic programming approach, IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(11): 5208\u20135221.","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"3429_CR15","doi-asserted-by":"publisher","first-page":"111261","DOI":"10.1016\/j.automatica.2023.111261","volume":"157","author":"O Qasem","year":"2023","unstructured":"Qasem O, Gao W N, and Vamvoudakis K G, Adaptive optimal control of continuous-time nonlinear affine systems via hybrid iteration, Automatica, 2023, 157: 111261.","journal-title":"Automatica"},{"issue":"12","key":"3429_CR16","doi-asserted-by":"publisher","first-page":"4164","DOI":"10.1109\/TAC.2016.2548662","volume":"61","author":"W N Gao","year":"2016","unstructured":"Gao W N and Jiang Z P, Adaptive dynamic programming and adaptive optimal output regulation of linear systems, IEEE Transactions on Automatic Control, 2016, 61(12): 4164\u20134169.","journal-title":"IEEE Transactions on Automatic Control"},{"issue":"11","key":"3429_CR17","doi-asserted-by":"publisher","first-page":"11916","DOI":"10.1109\/TCYB.2021.3086223","volume":"52","author":"Y Z Wu","year":"2022","unstructured":"Wu Y Z, Liang Q P, and Hu J P, Optimal output regulation for general linear systems via adaptive dynamic programming, IEEE Transactions on Cybernetics, 2022, 52(11): 11916\u201311926.","journal-title":"IEEE Transactions on Cybernetics"},{"key":"3429_CR18","doi-asserted-by":"publisher","unstructured":"Wang B J, Xu L, Yi X L, et al., Semiglobal suboptimal output regulation for heterogeneous multi-agent systems with input saturation via adaptive dynamic programming, IEEE Transactions on Neural Networks and Learning Systems, 2022, DOI: https:\/\/doi.org\/10.1109\/TNNLS.2022.3191673.","DOI":"10.1109\/TNNLS.2022.3191673"},{"issue":"3","key":"3429_CR19","doi-asserted-by":"publisher","first-page":"938","DOI":"10.1109\/TNNLS.2018.2850520","volume":"30","author":"W N Gao","year":"2019","unstructured":"Gao W N and Jiang Z P, Adaptive optimal output regulation of time-delay systems via measurement feedback, IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(3): 938\u2013945.","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"3429_CR20","doi-asserted-by":"publisher","unstructured":"Li H Y and Wei Q L, Data-driven optimal output cluster synchronization control of heterogeneous multi-agent systems, IEEE Transactions on Automation Science and Engineering, 2023, DOI: https:\/\/doi.org\/10.1109\/TASE.2023.3289950.","DOI":"10.1109\/TASE.2023.3289950"},{"key":"3429_CR21","doi-asserted-by":"crossref","unstructured":"Gao W N, Jiang Z P, Lewis F L, et al., Cooperative optimal output regulation of multi-agent systems using adaptive dynamic programming, 2017 American Control Conference (ACC), Seattle, 2017, 2674\u20132679.","DOI":"10.23919\/ACC.2017.7963356"},{"key":"3429_CR22","doi-asserted-by":"publisher","unstructured":"Zhang W G and Yan J, Adaptive constrained output feedback optimal consensus tracking for uncertain nonlinear multi-agent systems and its application, International Journal of Control, 2022, DOI: https:\/\/doi.org\/10.1080\/00207179.2022.2160826.","DOI":"10.1080\/00207179.2022.2160826"},{"key":"3429_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ins.2018.07.047","volume":"469","author":"Y Yang","year":"2018","unstructured":"Yang Y, Xu C, Yue D, et al., Output feedback tracking control of a class of continuous-time nonlinear systems via adaptive dynamic programming approach, Information Sciences, 2018, 469: 1\u201313.","journal-title":"Information Sciences"},{"issue":"8","key":"3429_CR24","first-page":"413","volume":"16","author":"J Huang","year":"2004","unstructured":"Huang J, Nonlinear output regulation: Theory and applications, Philadelphia: Society for Industrial and Applied Mathematics, 2004, 16(8): 413\u2013415.","journal-title":"Philadelphia: Society for Industrial and Applied Mathematics"},{"issue":"2","key":"3429_CR25","doi-asserted-by":"publisher","first-page":"549","DOI":"10.1109\/TNNLS.2019.2905715","volume":"31","author":"S P He","year":"2020","unstructured":"He S P, Fang H Y, Zhang M G, et al., Adaptive optimal control for a class of nonlinear systems: The online policy iteration approach, IEEE Transactions on Neural Networks and Learning Systems, 2020, 31(2): 549\u2013558.","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"4","key":"3429_CR26","doi-asserted-by":"publisher","first-page":"1062","DOI":"10.1109\/TAC.2011.2169618","volume":"57","author":"Y F Su","year":"2012","unstructured":"Su Y F and Huang J, Cooperative output regulation of linear multi-agent systems, IEEE Transactions on Automatic Control, 2012, 57(4): 1062\u20131066.","journal-title":"IEEE Transactions on Automatic Control"},{"issue":"1","key":"3429_CR27","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1109\/TAC.1968.1098829","volume":"13","author":"D Kleinman","year":"1968","unstructured":"Kleinman D, On an iterative technique for Riccati equation computations, IEEE Transactions on Automatic Control, 1968, 13(1): 114\u2013115.","journal-title":"IEEE Transactions on Automatic Control"},{"key":"3429_CR28","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511804441","volume-title":"Convex Optimization","author":"S Boyd","year":"2004","unstructured":"Boyd S and Vandenberghe L, Convex Optimization, Cambridge University Press, Cambridge, 2004."},{"key":"3429_CR29","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781107298019","volume-title":"Understanding Machine Learning: From Theory to Algorithms","author":"S S Shwartz","year":"2014","unstructured":"Shwartz S S and Ben D S, Understanding Machine Learning: From Theory to Algorithms, Cambridge University Press, Cambridge, 2014."},{"issue":"2","key":"3429_CR30","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1137\/16M1080173","volume":"60","author":"L Bottou","year":"2016","unstructured":"Bottou L, Curtis F E, and Nocedal J, Optimization methods for large-scale machine learning, SIAM Review, 2016, 60(2): 223\u2013311.","journal-title":"SIAM Review"}],"container-title":["Journal of Systems Science and Complexity"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11424-024-3429-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11424-024-3429-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11424-024-3429-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,27]],"date-time":"2024-02-27T04:59:20Z","timestamp":1709009960000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11424-024-3429-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2]]},"references-count":30,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,2]]}},"alternative-id":["3429"],"URL":"https:\/\/doi.org\/10.1007\/s11424-024-3429-0","relation":{},"ISSN":["1009-6124","1559-7067"],"issn-type":[{"value":"1009-6124","type":"print"},{"value":"1559-7067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2]]},"assertion":[{"value":"13 October 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 November 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 February 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no conflict of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}}]}}