Neural adaptive fault-tolerant finite-time control for nonstrict feedback systems: An event-triggered mechanism

2021 ◽  
Author(s):  
Kangkang Sun ◽  
Jianbin Qiu ◽  
Hamid Reza Karimi
2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Haibo Xie ◽  
Zhengjiang Liu ◽  
Chengyong Yan ◽  
Shibo Zhou

This paper investigates the distributed finite-time event-triggered bipartite consensus control for multiagent systems over antagonistic networks. Under the constraint of energy conservation, a distributed nonlinear finite-time control protocol only depending upon local information is proposed coupled with event-triggered strategies, where controllers of agents at triggered instants are only updated to reduce the computation. It is proved that when the antagonistic network is structurally balanced with a spanning tree, a necessary and sufficient condition is established to guarantee all agents to reach consensus values with identical magnitude but opposite signs. More interestingly, the settling time depending on the initial state is obtained over the whole process. Comparing to asymptotic control algorithms, the proposed control method has better disturbance rejection properties and convergence rate. Simulations are given to demonstrate the effectiveness of the theoretical results.


Author(s):  
Hangli Ren ◽  
Guangdeng Zong

This article addresses the finite-time control problem for a class of switched linear parameter-varying systems via an event-triggered communication scheme. Different from the existing finite-time problems, not only the problem of finite-time boundedness but also the problem of input-output finite-time stability is considered in this article. Using an asynchronous switching scheme, sufficient conditions are established to guarantee the event-based closed-loop systems are both finite-time bounded and input-output finite-time stable. Then, a parameter-dependent asynchronous controller is designed by solving a set of linear matrix inequalities. Finally, a numerical example is presented to show the effectiveness of the result.


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