Formation Tracking for Nonaffine Nonlinear Multiagent Systems Using Neural Network Adaptive Control
Adaptive tracking control for distributed multiagent systems in nonaffine form is considered in this paper. Each follower agent is modeled by a nonlinear pure-feedback system with nonaffine form, and a nonlinear system is unknown functions rather than constants. Radial basis function neural networks...
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| Veröffentlicht in: | Mathematical problems in engineering 2020, Vol.2020 (2020), p.1-8 |
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| creator | Zhao, Tongjuan Zhang, Jianhua Wang, Jiuhe |
| description | Adaptive tracking control for distributed multiagent systems in nonaffine form is considered in this paper. Each follower agent is modeled by a nonlinear pure-feedback system with nonaffine form, and a nonlinear system is unknown functions rather than constants. Radial basis function neural networks (NNs) are employed to approximate the unknown nonlinear functions, and weights of NNs are updated by adaptive law in finite-time form. Then, the adaptive finite NN approach and backstepping technology are combined to construct the consensus tracking control protocol. Numerical simulation is presented to demonstrate the efficacy of suggested control proposal. |
| doi_str_mv | 10.1155/2020/3697476 |
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Each follower agent is modeled by a nonlinear pure-feedback system with nonaffine form, and a nonlinear system is unknown functions rather than constants. Radial basis function neural networks (NNs) are employed to approximate the unknown nonlinear functions, and weights of NNs are updated by adaptive law in finite-time form. Then, the adaptive finite NN approach and backstepping technology are combined to construct the consensus tracking control protocol. Numerical simulation is presented to demonstrate the efficacy of suggested control proposal.</description><identifier>ISSN: 1024-123X</identifier><identifier>EISSN: 1563-5147</identifier><identifier>DOI: 10.1155/2020/3697476</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Adaptive control ; Artificial intelligence ; Inequality ; Mathematical models ; Multiagent systems ; Neural networks ; Nonlinear systems ; Radial basis function ; Topography ; Tracking control</subject><ispartof>Mathematical problems in engineering, 2020, Vol.2020 (2020), p.1-8</ispartof><rights>Copyright © 2020 Tongjuan Zhao et al.</rights><rights>Copyright © 2020 Tongjuan Zhao et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Wiley-Blackwell Open Access Titles; Alma/SFX Local Collection |
| subjects | Adaptive control Artificial intelligence Inequality Mathematical models Multiagent systems Neural networks Nonlinear systems Radial basis function Topography Tracking control |
| title | Formation Tracking for Nonaffine Nonlinear Multiagent Systems Using Neural Network Adaptive Control |
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