题目：Output Stabilization of an ODE-Heat Cascade System by Neural Operator Approximations

报告人：王军民 教授（北京理工大学）

地点：致远楼103室

时间：2026年5月20日 星期三 09：45

Abstract：In this talk, we introduce the output feedback stabilization of an ordinary differential equation (ODE)-heat cascade system with a variable coefficient reaction term. We design the boundary feedback controller by backstepping method, where the control design is accelerated by neural operators. Through DeepONet approximation of nonlinear operator, we prove the existence of kernel PDEs under DeepONet arbitrary accuracy approximation. Then we design the DeepONet-approximated observer and output feedback controller, and demonstrate the output feedback stability of the closed-loop system under DeepONet approximations. Numerical simulations verify the effectiveness of the controller and illustrate that this method is two orders of magnitude faster than PDE solvers.

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