Distributed adaptive asymptotically consensus tracking control of uncertain Euler-Lagrange systems under directed graph condition

2017 ◽  
Vol 71 ◽  
pp. 121-129 ◽  
Author(s):  
Wei Wang ◽  
Changyun Wen ◽  
Jiangshuai Huang ◽  
Huijin Fan
Keyword(s):  
Directed Graph ◽  
Tracking Control ◽  
Consensus Tracking

Command filtered backstepping tracking control of uncertain nonlinear strict-feedback systems under a directed graph

2016 ◽  
Vol 39 (7) ◽  
pp. 1027-1036 ◽  
Author(s):  
Yi Zhang ◽  
Guozeng Cui ◽  
Guangming Zhuang ◽  
Junwei Lu ◽  
Ze Li
Keyword(s):  
Directed Graph ◽  
Tracking Control ◽  
Design Procedure ◽  
Design Parameters ◽  
Feedback Systems ◽  
Consensus Tracking ◽  
Backstepping Approach ◽  
Non Linear ◽  
Distributed Controllers ◽  
Strict Feedback

This paper studies the distributed consensus tracking control problem of multiple uncertain non-linear strict-feedback systems under a directed graph. The command filtered backstepping approach is utilised to alleviate computation burdens and construct distributed controllers, which involves compensated signals eliminating filtered error effects in the design procedure. Neural networks are employed to estimate uncertain non-linear items. Using a Lyapunov stability theorem, it is proved that all signals in the closed-looped systems are semi-globally uniformly ultimately bounded. In addition, consensus errors converge to a small neighbourhood of the origin by adjusting the appropriate design parameters. Finally, simulation results are presented to demonstrate the effectiveness of the developed control design approach.

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