{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T16:54:00Z","timestamp":1776963240422,"version":"3.51.4"},"reference-count":30,"publisher":"Cambridge University Press (CUP)","issue":"1","license":[{"start":{"date-parts":[[2017,4,3]],"date-time":"2017-04-03T00:00:00Z","timestamp":1491177600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotica"],"published-print":{"date-parts":[[2018,1]]},"abstract":"<jats:title>SUMMARY<\/jats:title><jats:p>This paper addresses the formation tracking control of a group of tractor\u2013trailer systems in the presence of model uncertainties. A virtual leader\u2013follower formation technique is used to design a controller in order to force a team of tractor\u2013trailer systems to construct a desired formation configuration. Since tractor\u2013trailer systems have a nonlinear multi-input multi-output model with strong couplings, multi-layer neural networks are employed to overcome unknown nonlinearities and uncertain parameters by using on-line weight tuning algorithms. Neural network approximation errors and external disturbances are also compensated with adaptive robust signals. The dynamic surface control approach has been used to reduce the complexity of the proposed controller effectively. Lyapunov\u2019s direct method proves that all signals in the closed-loop formation control system are bounded and tracking errors converge to a neighborhood of the origin whose size is adjustable. Finally, simulation results will be provided to illustrate the efficiency of the proposed controller.<\/jats:p>","DOI":"10.1017\/s0263574717000145","type":"journal-article","created":{"date-parts":[[2017,4,3]],"date-time":"2017-04-03T11:44:25Z","timestamp":1491219865000},"page":"39-56","source":"Crossref","is-referenced-by-count":33,"title":["Neural network formation control of a team of tractor\u2013trailer systems"],"prefix":"10.1017","volume":"36","author":[{"given":"Khoshnam","family":"Shojaei","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2017,4,3]]},"reference":[{"key":"S0263574717000145_ref022","doi-asserted-by":"publisher","DOI":"10.1109\/TCST.2014.2321514"},{"key":"S0263574717000145_ref014","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2011.2105475"},{"key":"S0263574717000145_ref004","doi-asserted-by":"publisher","DOI":"10.1109\/TCST.2007.908214"},{"key":"S0263574717000145_ref009","doi-asserted-by":"publisher","DOI":"10.1109\/TCST.2012.2200484"},{"key":"S0263574717000145_ref002","doi-asserted-by":"publisher","DOI":"10.1109\/TRA.2002.803458"},{"key":"S0263574717000145_ref003","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008814708459"},{"key":"S0263574717000145_ref006","doi-asserted-by":"publisher","DOI":"10.1049\/iet-cta:20050371"},{"key":"S0263574717000145_ref025","doi-asserted-by":"publisher","DOI":"10.1007\/s10514-005-4750-7"},{"key":"S0263574717000145_ref001","doi-asserted-by":"publisher","DOI":"10.1109\/70.736776"},{"key":"S0263574717000145_ref028","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1109\/TNN.2003.813823","article-title":"Neural-network control of nonaffine nonlinear system with zeros dynamics by state and output feedback","volume":"14","author":"Ge","year":"2003","journal-title":"IEEE Trans. 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