{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,6,24]],"date-time":"2024-06-24T05:10:56Z","timestamp":1719205856209},"reference-count":34,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2024,3,29]],"date-time":"2024-03-29T00:00:00Z","timestamp":1711670400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,6,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>This paper considers the adaptive two-bit-triggered containment control problem for nonlinear multi-agent systems in the presence of input saturation. Since input saturation occurs frequently in practical systems, which can affect the stability of the multi-agent systems under consideration, an auxiliary design system is introduced to address this issue. Meanwhile, considering limited transmission resources in practical systems, this paper mainly focuses on the triggering condition and the control signal transmission bits, presenting a two-bit-triggered control approach to optimize the utilization of transmission resources. Furthermore, a command filter is introduced into the design process to solve the problem of complexity explosion. The proposed method ensures that all signals of the closed-loop system are bounded and the output signals of all followers converge to a convex hull spanned by the outputs of the leaders. Finally, two simulation examples are provided to verify the validity of the presented control scheme.<\/jats:p>","DOI":"10.1093\/imamci\/dnae010","type":"journal-article","created":{"date-parts":[[2024,3,30]],"date-time":"2024-03-30T15:20:39Z","timestamp":1711812039000},"page":"275-298","source":"Crossref","is-referenced-by-count":0,"title":["Command filter-based adaptive neural two-bit-triggered containment control for saturated nonlinear multi-agent systems"],"prefix":"10.1093","volume":"41","author":[{"given":"Yuhang","family":"Wu","sequence":"first","affiliation":[{"name":"College of Control Science and Engineering, Bohai University , Jinzhou, Liaoning 121013 , China"}]},{"given":"Ben","family":"Niu","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shandong Normal University , Jinan 250014 , China"}]},{"given":"Ning","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Bohai University , Jinzhou, Liaoning 121013 , China"}]},{"given":"Xudong","family":"Zhao","sequence":"additional","affiliation":[{"name":"Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology , Dalian 116024, Liaoning , China"}]},{"given":"Adil M","family":"Ahmad","sequence":"additional","affiliation":[{"name":"Communication Systems and Networks Research Group , Faculty of Computing and Information Technology, Department of Information Technology, , Jeddah 22254 , Saudi Arabia"},{"name":"King Abdulaziz University , Faculty of Computing and Information Technology, Department of Information Technology, , Jeddah 22254 , Saudi Arabia"}]}],"member":"286","published-online":{"date-parts":[[2024,3,29]]},"reference":[{"key":"2024062404304106500_ref1","doi-asserted-by":"crossref","first-page":"1865","DOI":"10.1007\/s11071-016-2801-6","article-title":"H consensus of nonlinear multi-agent systems using dynamic output feedback controller: an LMI approach","volume":"85","author":"Amini","year":"2016","journal-title":"Nonlinear Dynam."},{"key":"2024062404304106500_ref19","doi-asserted-by":"crossref","DOI":"10.1002\/adts.202301136","article-title":"Adaptive output feedback control for uncertain nonlinear systems with unknown modeling errors","author":"Cai","year":"2024","journal-title":"Advanced Theory and Simulations"},{"key":"2024062404304106500_ref4","doi-asserted-by":"crossref","first-page":"2086","DOI":"10.1109\/TNNLS.2014.2360933","article-title":"Dynamic surface control using neural networks for a class of uncertain nonlinear systems with input saturation","volume":"26","author":"Chen","year":"2014","journal-title":"IEEE Trans. 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