Event-triggered finite-time dissipative control for fractional-order neural networks with uncertainties

被引：0
作者：
Nguyen Thi Thanh Huyen
Tran Ngoc Tuan
Mai Viet Thuan
Nguyen Truong Thanh
机构：
[1] TNU–University of Sciences,Department of Mathematics and Informatics
[2] Hung Yen University of Technology and Education,Department of Basic Science
[3] Hanoi University of Science and Technology,School of Applied Mathematics and Informatics
来源：
Neural Processing Letters | / 56卷
关键词：
Finite-time dissipative; Event-triggered control; Fractional-order neural networks; Uncertainties; Linear matrix inequalities; 34D10; 93D15; 49M7; 34K20;
D O I：
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摘要：
In this paper, the focus is on addressing the problems of designing an event-triggered finite-time dissipative control strategy for fractional-order neural networks (FONNs) with uncertainties. Firstly, the Zeno behavior of the fractional-order neural networks model is discussed. Utilizing inequality techniques, we calculate a positive lower bound for inter-execution intervals, which serves to resolve issues related to infinite triggering and sampling. Secondly, we formulate an event-triggered control scheme to solve the finite-time dissipative control problems. Through the application of finite-time boundedness theory, fractional-order calculus properties, and linear matrix inequality techniques, we derive sufficient conditions for the existence of such an event-triggered finite-time dissipative state-feedback control for the considered systems. Finally, a numerical example is given to demonstrate the effectiveness of the proposed methodology.
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