Consensus of Multi-Agent Systems With General Linear and Lipschitz Nonlinear Dynamics Using Distributed Adaptive Protocols
Zhongkui Li, Wei Ren, Xiangdong Liu, Mengyin Fu
Peking University University of California, Riverside Beijing Institute of Technology
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This technical brief considers the distributed consensus problems for multi-agent systems with general linear and Lipschitz nonlinear dynamics. Distributed relative-state consensus protocols with an adaptive law for adjusting the coupling weights between neighboring agents are designed for both the linear and nonlinear cases, under which consensus is reached for all undirected connected communication graphs. Extensions to the case with a leader-follower communication graph are further studied. In contrast to the existing results in the literature, the adaptive consensus protocols here can be implemented by each agent in a fully distributed fashion without using any global information.
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计算机 / AIDistributed Control Multi-Agent Systems
Neural Networks Stability and Synchronization · Advanced Memory and Neural Computing
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