a The Key Laboratory for Advanced Process Control of Light Industry of the Ministry of Education, School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China; b The State Key Laboratory for Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Abstract This paper is concerned with the stochastic bounded consensus tracking problems of leader-follower multi-agent systems, where the control input of an agent can only use the information measured at the sampling instants from its neighbours or the virtual leader with a time-varying reference state, and the measurements are corrupted by random noises. The probability limit theory and the algebra graph theory are employed to derive the necessary and sufficient condition guaranteeing the mean square bounded consensus tracking. It is shown that the maximum allowable upper bound of the sampling period simultaneously depends on the constant feedback gains and the network topology. Furthermore, the effects of the sampling period on the tracking performance are analysed. It turns out that from the view point of the sampling period, there is a trade-off between the tracking speed and the static tracking error. Simulations are provided to demonstrate the effectiveness of the theoretical results.
Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 61203147, 60973095, 60804013, and 61104092), the Fundamental Research Funds for the Central Universities, China (Grant Nos. JUSRP111A44, JUSRP21011, and JUSRP11233), the Foundation of State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology (HUST), China (Grant No. DMETKF2010008), and the Humanities and Social Sciences Youth Funds of the Ministry of Education, China (Grant No. 12YJCZH218).
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