New distributed adaptive protocols for uncertain nonlinear leader-follower multi-agent systems via a repetitive learning control approach |
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| Institution: | 1. School of Mathematics and Statistics, Xidian University, Xi’an 710071, PR China;2. School of Science, Lanzhou University of Technology, Lanzhou 730050, PR China;1. School of Automation, Guangdong University of Technology, Guangzhou, Guangdong 510006, China;2. School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong 510006, China;3. Navigation College, Dalian Maritime University, Dalian 116026, China;1. Department of Mathematics, Huizhou University, Guangdong 516007, China;2. School of Automation, Key Laboratory of Image Processing and Intelligent Control, Huazhong University of Science and Technology, Hubei 430074, China |
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| Abstract: | In this paper, the distributed consensus problem of leader-follower multi-agent systems with unknown time-varying coupling gains and parameter uncertainties are investigated, and the fully distributed protocols with the adaptive updating laws of periodic time-varying parameters are designed by using a repetitive learning control approach. By virtue of algebraic graph theory, Barbalat’s lemma and an appropriate Lyapunov-Krasovskii functional, it is shown that each follower agent can asymptotically track the leader even though the dynamic of the leader is unknown to any of them, i.e., the global asymptotic consensus can be achieved. At last, a simulation example is given to illustrate the feasibility and efficiency of the proposed protocols. |
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