Abstract:
This paper revisits the distributed adaptive control problem for synchronization of multi-agent systems where the dynamics of the agents are nonlinear, nonidentical, unkn...Show MoreMetadata
Abstract:
This paper revisits the distributed adaptive control problem for synchronization of multi-agent systems where the dynamics of the agents are nonlinear, nonidentical, unknown and subject to external disturbances. The communication topology under consideration is represented by a fixed strongly-connected directed graph. Distributed neural networks are used to approximate the uncertain dynamics and decentralized control protocols using local neighborhood information are proposed to solve the cooperative tracker problem, the problem of synchronization of all follower agents to a leader agent. In particular, we show that, under the proposed decentralized control protocols, the synchronization errors are ultimately bounded and their ultimate bounds can be reduced arbitrarily by choosing the control parameter appropriately.
Published in: 2014 American Control Conference
Date of Conference: 04-06 June 2014
Date Added to IEEE Xplore: 21 July 2014
ISBN Information: