DocumentCode :
550565
Title :
Distributed containment control for multiple nonlinear systems with identical dynamics
Author :
Mei Jie ; Ren Wei ; Ma Guangfu
Author_Institution :
Harbin Inst. of Technol., Harbin, China
fYear :
2011
fDate :
22-24 July 2011
Firstpage :
6544
Lastpage :
6549
Abstract :
In this paper, we study the distributed containment control problem for multiple nonlinear systems with multiple dynamic leaders. The objective is that a team of followers converges to the convex hull spanned by multiple dynamic leaders with identical dynamics as the followers. The strategy has many applications such as securing a group of followers in the area spanned by the leaders so that they can be away from dangerous sources outside the area. We first propose a control algorithm to achieve the objective under a directed graph. To compensate the drawback that the control gain of the control algorithm under a directed graph has a lower bound depending on the Laplacian matrix, we then propose an adaptive control gain design using only local information of the followers´ neighbors. Therefore, the proposed control algorithm for the containment control problem is totally distributed under the condition that the interaction among the followers is undirected. Finally, simulation examples are provided to show the effectiveness of the proposed control algorithms.
Keywords :
adaptive control; decentralised control; distributed control; graph theory; matrix algebra; nonlinear control systems; Laplacian matrix; adaptive control; directed graph; distributed containment control; dynamic leaders; gain control; identical dynamics; multiple nonlinear systems; Algorithm design and analysis; Distributed control; Eigenvalues and eigenfunctions; Heuristic algorithms; Laplace equations; Lead; Nonlinear systems; Containment Control; Cooperative Control; Distributed Control; Multi-agent Systems; Nonlinear Systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
ISSN :
1934-1768
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
Type :
conf
Filename :
6000904
Link To Document :
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