Distributed asymptotically synchronization control for MIMO nonlinear multiagent systems
This paper deals with the synchronization control of multiagent systems with nonlinear multiple-input multiple-output(MIMO) agent dynamics. A novel indirect neural distributed synchronization scheme with asymptotic synchronization error is proposed. The main contribution lies in the fact that both nonlinear MIMO agent dynamics with unknown control gain matrix function, which makes most existing agent dynamics as special cases, and asymptotic synchronization error are considered. The system uncertainties are compensated by neural networks in an online manner. In order to address the singularity problem caused by unknown control gain matrices, we have introduced a novel Lyapunov function candidate. Meanwhile, a robust term is introduced to achieve asymptotic synchronization error. The stability results are guaranteed via Lyapunov analysis. Finally, the effectiveness of the proposed controller is verified through a three-agent example.
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|15th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2018|
|Organisation||Department of Systems and Computer Engineering|
Meng, W. (Wenchao), Zhang, H. (Heng), Zhou, H. (Huan), & Liu, P. (2019). Distributed asymptotically synchronization control for MIMO nonlinear multiagent systems. In Proceedings - 2018 15th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2018 (pp. 31–37). doi:10.1109/I-SPAN.2018.00015