Adaptive Neural Consensus Tracking for Nonlinear Multiagent Systems Using Finite-Time Command Filtered Backstepping

2018 ◽  
Vol 48 (11) ◽  
pp. 2003-2012 ◽  
Author(s):  
Lin Zhao ◽  
Jinpeng Yu ◽  
Chong Lin ◽  
Yumei Ma
2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Nan Liu ◽  
Rui Ling ◽  
Qin Huang ◽  
Zheren Zhu

Consensus tracking problem of the leader-follower multiagent systems is resolved via second-order super-twisting sliding mode control approach. The followers’ states can keep consistent with the leader’s states on sliding surfaces. The proposed approach can ensure the finite-time consensus if the directed graph of the nonlinear system has a directed path under the condition that leader’s control input is unavailable to any followers. It is proved by using the finite-time Lyapunov stability theory. Simulation results verify availability of the proposed approach.


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