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Thời gian: 8h30 ngày 8/11/2023, seminar Toán ứng dụng và Giải tích sẽ tiếp tục tại VPK Toán - Tin
Báo cáo viên: NCS. Trần Ngọc Tuấn
Tên báo cáo: Event-triggered finite-time dissipative control for fractional-order neural networks with uncertainties. 

Tóm tắt: In this paper, the focus is on addressing the problems of designing an eventtriggered 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 interexecution 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, fractionalorder 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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