Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Consensus of multiagent systems and synchronization of complex networks: a unified viewpoint
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Brief paper: Distributed adaptive control for synchronization of unknown nonlinear networked systems
Automatica (Journal of IFAC)
Tracking control for multi-agent consensus with an active leader and variable topology
Automatica (Journal of IFAC)
Adaptive cooperative tracking control of higher-order nonlinear systems with unknown dynamics
Automatica (Journal of IFAC)
| Hi-index | 0.01 |
In this paper, a distributed adaptive control architecture is proposed for cooperative tracking of uncertain dynamical multi-agent systems over an undirected network. Adaptive cooperative tracking controllers with both static and adaptive coupling gains are developed using local information obtained from neighboring agents. Neural networks together with filtering adaptive laws are employed to enable fast learning in the presence of unmodeled uncertainties and external disturbances. Moreover, this result is extended to the output feedback case in which only partial state information of each agent can be measured. Observer-based adaptive cooperative tracking controllers with static and adaptive coupling are developed, and a parameter dependent Riccati equation is employed to derive the stability of the overall multi-agent systems. Compared with the existing results, a distinct feature of the developed controllers enables fast learning using large adaptive gains with guaranteed low frequency control signals. Two illustrative examples are given to validate the efficacy of the proposed approaches.