Multi-event triggered sliding mode control for a class of complex neural networks

2021 ◽  
Vol 96 ◽  
pp. 107506
Author(s):  
Guangchen Zhang ◽  
Xufei Li ◽  
Yuanqing Xia
2021 ◽  
Author(s):  
Junchao Ren ◽  
xuejiao Li

Abstract This paper investigates the projection synchronization problem of stochastic neural networked systems based on event-triggered sliding mode control (SMC) covering a finite-time period. For improve transmission efficiency and save network resources, a related event-triggered scheme is proposed for the error system, which can identify whether the measurement error should be transmitted to the controller. For finite-time projective synchronization under given event-triggered mechanism, a semi-Markov jump system model is proposed. Secondly, by creating Lyapunov Krasovsky functional and using linear matrix inequality (LMI) technology, as well as considering a proper sliding surface, a sliding mode controller is designed to implement finite-time projection synchronization of different neural networks. Finally, numerical simulations are exploited to illustrate the effectiveness of the main results.


2020 ◽  
Vol 53 (2) ◽  
pp. 6207-6212
Author(s):  
Kiran Kumari ◽  
Bijnan Bandyopadhyay ◽  
Johann Reger ◽  
Abhisek K. Behera

2016 ◽  
Vol 24 (5) ◽  
pp. 1048-1057 ◽  
Author(s):  
Shiping Wen ◽  
Tingwen Huang ◽  
Xinghuo Yu ◽  
Michael Z. Q. Chen ◽  
Zhigang Zeng

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