Adaptive consensus tracking for linear multi-agent systems with input saturation

2016 ◽  
Vol 38 (12) ◽  
pp. 1434-1441 ◽  
Author(s):  
Hongjun Chu ◽  
Weidong Zhang

This paper addresses the consensus protocol design problem for linear multi-agent systems with input saturation. Existing consensus protocols usually contain certain global information, such as network size or the spectrum of the Laplacian matrix, and this global knowledge is often unavailable to all agents. In this paper, based on only the agent dynamics and the relative states of neighbouring agents, a novel adaptive consensus protocol is designed by assigning a time-varying coupling weight to each node. This protocol has two advantages: it is independent of any global information, and hence is fully distributed; and it is implemented by actuators with input saturation constraints. By combining the low-gain feedback method and appropriate Lyapunov techniques, it is shown that our protocol can achieve the semi-global consensus tracking in a fully distributed fashion, under the mild assumptions on agent dynamics and the topology graph. The results are illustrated by numerical simulations

2019 ◽  
Vol 30 (07) ◽  
pp. 1940001 ◽  
Author(s):  
Xiaolu Liu ◽  
Duxin Chen ◽  
Yan-Wu Wang

This paper investigates the leader-follower exponential consensus problem of a class of Lipschitz nonlinear multi-agent systems (MASs) with input saturation. Since each agent has nonlinear dynamics, the system is not asymptotically null controllable with bounded controls. Therefore, the widely-used low-gain feedback method for designing consensus protocols of MASs with input saturation can no longer work. Taking advantage of the stability theory of impulsive systems and features of the Laplacian matrix, and combining the properties of convex hull, a distributed impulsive consensus protocol is proposed. Still, the shape reference set is introduced to assess the attraction domain of leader–follower MASs. Finally, a numerical experiment validates the effectiveness of the proposed anti-saturation impulsive consensus algorithm.


2020 ◽  
Vol 107 ◽  
pp. 194-205 ◽  
Author(s):  
Ateeq ur Rehman ◽  
Muhammad Rehan ◽  
Muhammad Riaz ◽  
Muhammad Abid ◽  
Naeem Iqbal

2021 ◽  
Vol 432 ◽  
pp. 183-193
Author(s):  
Zhen-Hua Zhu ◽  
Zhi-Hong Guan ◽  
Bin Hu ◽  
Ding-Xue Zhang ◽  
Xin-Ming Cheng ◽  
...  

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