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Adaptive Consensualization for Lipschitz Nonlinear-type Multi-agent Networks with Fixed Topologies
Tang Zheng,Jianxiang Xi,Mei Yuan,Guangbin Liu 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.4
Adaptive consensualization problems for Lipschitz nonlinear-type multi-agent networks with fixed topologies are addressed. By using the state errors of the neighboring agents, an adaptive consensus protocol is proposed to deal with the consensualization problems. To eliminate the impacts of the Lipschitz nonlinear dynamics, the structure property of a transformation matrix and the Laplacian matrix, and the Lipschitz condition are well utilized. In the Lyapunov function, a scaling constant is introduced to eliminate the impacts of eigenvalues of the Laplacian matrix, which are the global information of the whole multi-agent networks. Then, an completely distributed consensualization criterion is presented in terms of the linear matrix inequality. Furthermore, an explicit expression of the consensus function and its initial state of this multi-agent network are presented. In the Final, a numerical example is shown to verify the validity of theoretical results.
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Le Wang,Qing Chen,Jianxiang Xi,Guangbin Liu 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.5
The current paper studies the guaranteed-performance consensualization for general high-order multiagentsystems with intermittent communications. Firstly, a new consensus protocol is constructed by using only intermittentlocal information, and the corresponding performance function is given to guarantee the consensus regulationperformance among neighboring agents. Then, linear matrix inequality conditions for guaranteed-performanceconsensus and consensualization are respectively provided and a guaranteed-performance cost of multi-agent systemsis determined meanwhile. Furthermore, the whole motion mode of the multi-agent system can be described byderiving a precise expression of the consensus function. If the nominal converge rate is larger than a positive threshold,then multi-agent systems can achieve guaranteed-performance consensus by determining the gain matrix whenintermittent communications are involved, and the performance function is less than the guaranteed-performancecost. Finally, a simulation example is shown to demonstrate the effectiveness of the proposed theorems.
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