Title :
Adaptive tracking control of leader-following multi-agent systems
Author :
Hanquan Lin;Qinglai Wei;Derong Liu
Author_Institution :
The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China
fDate :
4/1/2015 12:00:00 AM
Abstract :
In this paper, a distributed tracking controller with an adaptive law for adjusting coupling weights between neighboring agents is designed for leader-following multi-agent systems under fixed and switching topologies. In contrast to most existing literature where agents are integrators or double integrators, the dynamics of each agent is a general linear system in this paper. To handle this problem, the controller is based on Riccati inequalities. In traditional distributed static controllers, the coupling weight depends on the communication graph. However, coupling weights associated with the feedback gain matrix in our method are updated by state errors between neighboring agents. We further present the stability analysis of leader-following multi-agent systems under switching topology. Most traditional literature requires the graph to be connected anytime, while the communication graph is only assumed to be jointly connected in this paper. The design technique is based on Riccati inequalities and algebraic graph theory. Finally, simulations are given to show the validity of our method.
Keywords :
"Topology","Adaptive systems","Gain measurement","Adaptation models","Couplings","Switches","Lead"
Conference_Titel :
Information Science and Technology (ICIST), 2015 5th International Conference on
DOI :
10.1109/ICIST.2015.7288958