Virtual Interval Sensing: Toward Safe Bounds for Dynamical Systems

Người báo cáo: Đinh Ngọc Thạch (Conservatoire National des Arts et Métiers, Sorbonne University Alliance, Paris, France)

Thời gian: 09h00 - 09h25, thứ Tư ngày 15/7/2026

Địa điểm: Phòng 508 nhà A6 Viện Toán học

Tóm tắt báo cáo: This talk begins with a general introduction to virtual sensors (i.e., real-time algorithms known as observers), followed by an explanation of how the system’s positivity property can be exploited to design interval observers capable of handling uncertainties. I will then present a unified framework for virtual interval sensing for linear systems, based on the Kazantzis–Kravaris/Luenberger (KKL) observer paradigm. The approach relies on transforming the original system into a suitable target form that enables the direct design of a virtual interval sensor. The interval bounds obtained in the transformed coordinates are subsequently mapped back to the original system variables. Owing to the generality of the KKL framework, the proposed methodology offers a systematic and flexible design procedure.

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Xuất bản mới
Adam Czornik, Đoàn Thái Sơn, Nguyễn Thị Thu Sương, Pole Placement Theorem for Linear Measurable Time-Varying Control Systems with Single Input, SIAM Journal on Control and Optimization, Vol. 64, Iss. 4 (2026)
Đinh Nho Hào, Maxim Shishlenin, Van Ba Cong, Stable Numerical Solution to Multi-dimensional Nonlinear Inverse Heat Conduction Problems via Artificial Neural Networks, Lobachevskii Journal of Mathematics, Volume 47, pages 1213–1232 (2026)
Nguyễn Trung Thành, Gianluca Barone, Dat Tran, Đinh Nho Hào, All-at-once proximal alternating minimization method for an inverse medium scattering problem, Journal of Computational Physics, Article: 115187 Volume: Volume 565 (2026)