Extended adaptive event-triggered formation tracking control of a class of multi-agent systems with time-varying delay

2018 ◽  
Vol 316 ◽  
pp. 386-398 ◽  
Author(s):  
Tao Li ◽  
Zhipeng Li ◽  
Shaobo Shen ◽  
Shumin Fei
Author(s):  
Tao Li ◽  
Zhipeng Li ◽  
Haitao Zhang ◽  
Shumin Fei

This paper considers the problem on formation tracking control of second-order multi-agent systems (MASs) with communication time-varying delay. Sufficient conditions on the directed interaction topology and existence of the feedback gains to ensure the desired control are presented. Through choosing two augmented Lyapunov–Krasovskii (L–K) functionals and using some novel Wirtinger-based integral inequalities, the previously ignored information can be reconsidered and the application area of derived results can be greatly extended. Moreover, a novel constructive technique is given to compute out the controller gain by resorting to solving the achieved linear matrix inequalities (LMIs). Finally, a numerical example with comparisons and simulations is provided to illustrate the obtained results.


2020 ◽  
Vol 09 (01) ◽  
pp. 23-34
Author(s):  
Xiaofeng Chai ◽  
Jian Liu ◽  
Yao Yu ◽  
Jianxiang Xi ◽  
Changyin Sun

In this paper, we study the practical fixed-time event-triggered time-varying formation tracking problem of leader-follower multi-agent systems with multi-dimensional dynamics. Fixed-time event-triggered control schemes with continuous communication and intermittent communication are developed, respectively. Continuous communication and measurement are avoided, and computation cost is reduced greatly in the latter scheme. And the settling time is to be specified regardless of initial states of agents. Meanwhile, tracking errors are adjustable as desired with expected settling time. It is demonstrated that time-varying formation tracking can be achieved under the two proposed control schemes and Zeno behavior can be excluded. Finally, numerical examples are provided to illustrate the effectiveness of the proposed control strategies.


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