Title :
Distributed adaptive tracking on Lagrangian systems with reduced interaction
Author :
Yuchen Liu ; Hao Fang ; Yutian Mao
Author_Institution :
Sch. of Autom., Beijing Inst. of Technol., Beijing, China
Abstract :
In this paper, we propose a distributed adaptive approach for tracking problem without using leader´s velocity information, where agents are modeled by Euler-Lagrange equations. It is assumed that only a small fraction of agents within the leader´s communication range are informed about the position of the leader. Without using the leader´s velocity information, a connectivity-preserving adaptive controller is proposed to achieve tracking control on Lagrangian systems with the leader of constant velocity. Moreover, position and velocity consensus can be achieved asymptotically with the proposed control strategy. Numerical simulations are further provided to illustrate the theoretical results.
Keywords :
adaptive control; distributed control; multi-agent systems; multi-robot systems; numerical analysis; position control; velocity control; Euler-Lagrange equation; Lagrangian system; control strategy; distributed adaptive tracking; leader communication range; leader position; leader velocity information; numerical simulation; position consensus; tracking control; velocity consensus; Automation; Intelligent control; Adaptive control; Distributed control; Lagrangian systems; Reduced interaction; Tracking;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
DOI :
10.1109/WCICA.2014.7053127