Distributed asymptotic consensus control of linearly parameterized multiagent systems with unknown control gain
A class of linearly parameterized multiagent systems with unknown parameters and unknown control gain are investigated in this paper. An adaptive algorithm is implemented for such multiagent systems to obtain consensus. In most previous cases, consensus approaches usually induce uniformly ultimately bounded consensus error because of the uncertainties existing in the system dynamics. By contrast, this paper introduces a novel robust consensus algorithm which can ensure that the consensus error converges to zero asymptotically. More specifically, an adaptive controller will be designed for on-line unknown parameter identification, and a robust continuous term will be applied to ease the effects of the external disturbances. Besides, the control signal is insured continuously to neglect actuator bandwidth requirement and avoid the caused chattering phenomenon. Noting that, for multiagent systems studied in this paper, each agent only needs to exchange information with its neighbor agents, i.e., the proposed consensus algorithm is distributed. The theoretical verification of asymptotic consensus result is given through Lyapunov synthesis and several simulation tests on a linearly parameterized multiagent system are conducted to demonstrate the performance of the algorithm.
|Keywords||adaptive control, consensus, distributed control, linearly parameterized, uncertainty|
|Conference||36th Chinese Control Conference, CCC 2017|
Li, J. (Jinglan), Meng, W. (Wenchao), Zhong, Z. (Zhiguang), & Yang, Q. (Qinmin). (2017). Distributed asymptotic consensus control of linearly parameterized multiagent systems with unknown control gain. In Chinese Control Conference, CCC (pp. 8851–8856). doi:10.23919/ChiCC.2017.8028764