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Volume 5 Issue 1
Jan.  2018

IEEE/CAA Journal of Automatica Sinica

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Yang Yang and Dong Yue, "Distributed Tracking Control of a Class of Multi-agent Systems in Non-affine Pure-feedback Form Under a Directed Topology," IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 169-180, Jan. 2018. doi: 10.1109/JAS.2017.7510382
Citation: Yang Yang and Dong Yue, "Distributed Tracking Control of a Class of Multi-agent Systems in Non-affine Pure-feedback Form Under a Directed Topology," IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 169-180, Jan. 2018. doi: 10.1109/JAS.2017.7510382

Distributed Tracking Control of a Class of Multi-agent Systems in Non-affine Pure-feedback Form Under a Directed Topology

doi: 10.1109/JAS.2017.7510382
Funds:

the National Natural Science Foundation of China 61503194

the National Natural Science Foundation of China 61533010

the National Natural Science Foundation of China 61374055

the Ph.D. Programs Foundation of Ministry of Education of China 20110142110036

the Natural Science Foundation of Jiangsu Province BK20131381

the Natural Science Foundation of Jiangsu Province BK20140877

China Postdoctoral Science Foundation 2015M571788

Jiangsu Planned Projects for Postdoctoral Research Funds 1402066B

the Foundation of the Key Laboratory of Marine Dynamic Simulation and Control for the Ministry of Transport (DMU) DMUMSCKLT2016005

Jiangsu Government Scholarship for Overseas Studies 2017-037

the Key University Natural Science Research Project of Jiangsu Province 17KJA120003

the Scientific Foundation of Nanjing University of Posts and Telecommunications (NUPTSF) NY214076

More Information
  • In this paper, we consider a consensus tracking problem of a class of networked multi-agent systems (MASs) in non-affine pure-feedback form under a directed topology. A distributed adaptive tracking consensus control scheme is constructed recursively by the backstepping method, graph theory, neural networks (NNs) and the dynamic surface control (DSC) approach. The key advantage of the proposed control strategy is that, by the DSC technique, it avoids "explosion of complexity" problem along with the increase of the degree of individual agents and thus the computational burden of the scheme can be drastically reduced. Moreover, there is no requirement for prior knowledge about system parameters of individual agents and uncertain dynamics by employing NNs approximation technology. We then further show that, in theory, the designed control policy guarantees the consensus errors to be cooperatively semi-globally uniformly ultimately bounded (CSUUB). Finally, two examples are presented to validate the effectiveness of the proposed control strategy.

     

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