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Compared with the traditional optimal control algorithms for MASs, the proposed algorithm is designed on the basis of the event\u2010triggered scheme which can save the communication and computation resources. First, the consensus tracking problem is transferred into the input\u2010state stable (ISS) problem. Based on this, the event\u2010triggered condition for each agent is designed and the event\u2010triggered ADP is presented. Second, neural networks are introduced to simplify the application of the proposed algorithm. Third, the stability analysis of the MASs under the event\u2010triggered conditions is provided and the estimate errors of the neural networks\u2019 weights are also proved to be ultimately uniformly bounded. Finally, the simulation results demonstrate the effectiveness of the event\u2010triggered ADP consensus control method.<\/jats:p>","DOI":"10.1155\/2022\/6028054","type":"journal-article","created":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T14:20:07Z","timestamp":1646144407000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Event\u2010Triggered Adaptive Dynamic Programming Consensus Tracking Control for Discrete\u2010Time Multiagent Systems"],"prefix":"10.1155","volume":"2022","author":[{"given":"Yuyang","family":"Zhao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaolin","family":"Dai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dawei","family":"Gong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinzhi","family":"Lv","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7846-8901","authenticated-orcid":false,"given":"Yang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,3]]},"reference":[{"key":"e_1_2_10_1_2","doi-asserted-by":"publisher","DOI":"10.1109\/tac.2014.2309031"},{"key":"e_1_2_10_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/tac.2020.3010244"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/tii.2012.2216536"},{"key":"e_1_2_10_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/tsmc.2019.2920870"},{"key":"e_1_2_10_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/tase.2018.2874454"},{"key":"e_1_2_10_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCDS.2018.2866477"},{"key":"e_1_2_10_7_2","first-page":"3923","article-title":"Adaptive fault-tolerant tracking control for linear and lipschitz nonlinear multi-agent systems","volume":"62","author":"Zuo Z.","year":"2015","journal-title":"IEEE Transactions on Industrial Electronics"},{"key":"e_1_2_10_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/tsmc.2019.2962973"},{"key":"e_1_2_10_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/tcyb.2019.2963087"},{"key":"e_1_2_10_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/tie.2017.2701777"},{"key":"e_1_2_10_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/tsmc.2013.2295351"},{"key":"e_1_2_10_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2013.2281663"},{"key":"e_1_2_10_13_2","article-title":"Discrete-time nonlinear HJB solution using approximate dynamic programming","volume":"38","author":"Mu B.","year":"2008","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)"},{"key":"e_1_2_10_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/tfuzz.2014.2310238"},{"key":"e_1_2_10_15_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2015.2499757"},{"key":"e_1_2_10_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/tcsii.2018.2849639"},{"key":"e_1_2_10_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/tie.2016.2542134"},{"key":"e_1_2_10_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2728622"},{"key":"e_1_2_10_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/tcyb.2018.2819695"},{"key":"e_1_2_10_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/tsmc.2017.2758849"},{"key":"e_1_2_10_21_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.05.012"},{"key":"e_1_2_10_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.09.097"},{"key":"e_1_2_10_23_2","doi-asserted-by":"publisher","DOI":"10.1109\/tie.2019.2914571"},{"key":"e_1_2_10_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.amc.2019.01.066"},{"key":"e_1_2_10_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2019.2899594"},{"key":"e_1_2_10_26_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isatra.2019.01.021"},{"key":"e_1_2_10_27_2","doi-asserted-by":"publisher","DOI":"10.1109\/tcyb.2016.2523878"},{"key":"e_1_2_10_28_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isatra.2020.10.043"},{"key":"e_1_2_10_29_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2020.3009015"},{"key":"e_1_2_10_30_2","doi-asserted-by":"crossref","unstructured":"ChenM. 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