Volume 13, Issue 1 (Journal of Control, V.13, N.1 Spring 2019)                   JoC 2019, 13(1): 35-46 | Back to browse issues page


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Taj M, Shahriari-kahkeshi M. Adaptive Distributed Consensus Control for a Class of Heterogeneous and Uncertain Nonlinear Multi-Agent Systems. JoC 2019; 13 (1) :35-46
URL: http://joc.kntu.ac.ir/article-1-505-en.html
1- Shahrekord University, Faculty of Technology and Engineering
Abstract:   (6567 Views)

This paper has been devoted to the design of a distributed consensus control for a class of uncertain nonlinear multi-agent systems in the strict-feedback form. The communication between the agents has been described by a directed graph. Radial-basis function neural networks have been used for the approximation of the uncertain and heterogeneous dynamics of the followers as well as the effect of the neighbors of each agent in the multi-agent system. Then, the proposed scheme based on the dynamic surface control approach has been presented. Stability analysis of the closed-loop system shows that all the signals of the closed-loop system are uniformly ultimately bounded. The proposed scheme solves the consensus problem in the multi-agent systems with uncertain dynamics and avoids the "explosion of complexity" problem. The simulation results of the proposed approach are presented on a group of single-link robots with uncertain dynamics including four followers and one leader. The presented results verify the effectiveness of the proposed method.
 

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Type of Article: Research paper | Subject: Special
Received: 2017/07/21 | Accepted: 2018/05/30 | Published: 2019/07/15

References
1. [1] R. Olfati-Saber, J. A. Fax and R. M. Murray, "Consensus and cooperation in networked multi-agent systems," Proceedings of the IEEE, vol. 95, no. 1, pp. 215-233, 2007. [DOI:10.1109/JPROC.2006.887293]
2. [2] Y. Cao, W. Yu, W. Ren and G. Chen, "An overview of recentprogress in the study of distributed multi-agent coordination," IEEE Transaction on Industrial Information, vol. 9, no. 1, pp. 427-438, 2012. [DOI:10.1109/TII.2012.2219061]
3. [3] Y. Chen, J. Lu, X. Yu and D. J. Hill, "Multi-agent systems with dynamical topologies: consensus and applications," IEEE Circuits and Systems Magazine, vol. 13, no. 3, pp. 21-34, 2013. [DOI:10.1109/MCAS.2013.2271443]
4. [4] R. Olfati-Saber and R. M. Murray, "Consensus problems in networks of agents with switching topology and time-delays." IEEE Transactions on Automatic Control, vol. 49, no. 9, pp. 1520-1533, 2004. [DOI:10.1109/TAC.2004.834113]
5. [5] W. Ren, R. W. Beard and E. M. Atkins, "Information consensus in multivehicle cooperative control," IEEE Control Systems Magazine, vol. 27, no.2, pp. 71-82, 2007. [DOI:10.1109/MCS.2007.338264]
6. [6] H. Zhang, T. Feng, G. H. Yang and H. Liang, "Distributed cooperative optimal control for multiagent systems on directed graphs: An inverse optimal approach," IEEE Transactions on Cybernetics, vol. 45, no. 7, pp. 1315-1326, 2015. [DOI:10.1109/TCYB.2014.2350511]
7. [7] F. Xiao, L. Wang, J. Chen and Y. Gao, "Finite-time formation control for multi-agent systems," Automatica, vol. 45, pp. 2605-2611, 2009. [DOI:10.1016/j.automatica.2009.07.012]
8. [8] C. Q. Ma and J. F. Zhang, "Necessary and sufficient conditions for consensusability of linear multi-agent systems," IEEE Transactions on Automatic Control, vol. 55, no. 5, pp. 1263-1268, 2010. [DOI:10.1109/TAC.2010.2042764]
9. [9] F. Shamsi, H.A. Talebi and F. Abdollahi, "Output consensus control of multi-agent systems with nonlinear non-minimum phase dynamics," International Journal of Control, 2017. [DOI:10.1080/00207179.2017.1293847]
10. [10] C. L. P. Chen, C. E. Ren and T. Du, "Fuzzy observed-based adaptive consensus tracking control for second-order multi-agent systems with heterogeneous nonlinear dynamics," IEEE Transaction on Fuzzy Systems, vol. 24, no. 4, pp. 906-915,2016. [DOI:10.1109/TFUZZ.2015.2486817]
11. [11] H. Ma, Z. Wang, D. Wang, D. Liu, P. Yan and Q. Wei, "Neural-Network-Based distributed adaptive robust control for a class of nonlinear multi agent systems with time delays and external noises," IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 46, no. 6, pp. 750-758, 2016. [DOI:10.1109/TSMC.2015.2470635]
12. [12] C.L.P. Chen, G.X. Wen, Y.J. Liu and F.Y. Wang, "Adaptive consensus control for a class of nonlinear multiagent time-delay systems using neural networks," IEEE Transactions on Neural Networks and Learning Systems, Vol. 25, No. 6, pp. 1217-1226, 2014. [DOI:10.1109/TNNLS.2014.2302477]
13. [13] S. El-Ferik, A. Qureshi and F.L. Lewis, "Neuro-adaptive cooperative tracking control of unknown higher-order affine nonlinear systems," Automatica, vol. 50, pp. 798-808, 2014. [DOI:10.1016/j.automatica.2013.12.033]
14. [14] D. Zhao, T. Zou, S. Li and Q. Zhu, "Adaptive backstepping sliding mode control for leader-follower multi-agent systems," IET Control Theory and Applications, vol. 6, no. 8, pp. 1109-1117, 2012. [DOI:10.1049/iet-cta.2011.0001]
15. [15] G.X. Wen, C.L.P. Chen, Y.J. Liu and Z. Liu, "Neural-network-based adaptive leader-following consensus control for second-order non-linear multi-agent systems," IET Control Theory and Applications, vol. 9, no. 13, pp. 1927-1934, 2015. [DOI:10.1049/iet-cta.2014.1319]
16. [16] L. Zhao and Y. Jia, "Neural network-based adaptive consensus tracking control for multi-agent systems under actuator faults," International Journal of Systems Science, vol. 47, no. 8, pp. 1931-1942, 2016. [DOI:10.1080/00207721.2014.960906]
17. [17] G. Wang, C. Wang, Y. Yan, L. Li and X. Cai, "Distributed adaptive output feedback tracking control for a class of uncertain nonlinear multiagent systems," International Journal of Systems Science, vol. 48, no. 3, pp. 587-603, 2016. [DOI:10.1080/00207721.2016.1193261]
18. [18] W. Wang, C. Wen and J. Huang, "Distributed adaptive asymptotically consensus tracking control of nonlinear multi-agent systems with unknown parameters and uncertain disturbances" Automatica, Vol. 77, pp. 133-142, 2017. [DOI:10.1016/j.automatica.2016.11.019]
19. [19] Y. Zhang, G. Cui, G. Zhuang, J. Lu, and Z. Li, "Command filtered backstepping tracking control of uncertain nonlinear strict-feedback systems under a directed graph," Transactions of the Institute of Measurement and Control, 2016. [DOI:10.1177/0142331216629198]
20. [20] G. Cui, S. Xu, F.L. Lewis, B. Zhang and Q. Ma, "Distributed consensus tracking for non-linear multi-agent systems with input saturation: a command filtered backstepping approach," IET Control Theory and Applications, vol. 10, no. 5, pp. 509-516, 2016. [DOI:10.1049/iet-cta.2015.0627]
21. [21] X. Shi and S. Xu, "Adaptive distributed consensus tracking control for uncertain nonlinear multi-agent systems in pure-feedback form," in Control Conference (CCC), 2016 35th Chinese, 2016, pp. 475-479: IEEE. [DOI:10.1109/ChiCC.2016.7553130]
22. [22] X. Shi, J. Lu, Z. Li and S. Xu, "Robust adaptive distributed dynamic surface consensus tracking control for nonlinear multi-agent systems with dynamic uncertainties," Journal of the Franklin Institute, vol. 353, no. 17, pp. 4758-4805, 2016. [DOI:10.1016/j.jfranklin.2016.08.009]
23. [23] L. Zhang, C. Hua and X. Guan, "Distributed output feedback consensus tracking prescribed performance control for a class of nonlinear multi-agent systems with unknown disturbances," IET Control Theory and Applications, vol. 10, no. 8, pp. 877-883, 2016. [DOI:10.1049/iet-cta.2015.1120]
24. [24] S.J. Yoo, "distributed consensus tracking for multiple uncertain nonlinear strict-feedback systems under a directed graph," IEEE Transactions on Neural Networks and Learning Systems, vol. 24, no. 4, pp. 666-672, 2013. [DOI:10.1109/TNNLS.2013.2238554]
25. [25] D. Wang and J. Huang, "Neural network-based adaptive dynamic surface control for a class of uncertain nonlinear systems in strict-feedback form," IEEE Transactions on Neural Networks, vol. 16, no. 1, pp. 195-202, 2005. [DOI:10.1109/TNN.2004.839354]
26. [26] ح. حق‌شناس، م.ع. بادامچی‌زاده و م. برادران نیا، "کنترل محدود نگهدارندِه سیستم‌های چندعاملی خطی متشکل از عامل‌های غیر یکسان با استفاده از فیدبک خروجی دینامیکی،" مجله کنترل، جلد 10، شماره. 4، 1395.
27. [27] J. Park and I.W. Sandberg, "Universal approximation using radial-basis-function networks, Neural Computation," Neural computation, vol. 3, no. 2, pp. 246-257, 1991. [DOI:10.1162/neco.1991.3.2.246]

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