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A popular approach to designing finite-dimensional boundary controllers for partial differential equations (PDEs) is to decompose the PDE into independent modes and focus on the dominant ones while neglecting highly damped residual modes.…

Dynamical Systems · Mathematics 2025-07-18 Anton Selivanov , Emilia Fridman

Partial differential equations (PDEs) play a foundational role in modeling physical phenomena. This study addresses the challenging task of determining variable coefficients within PDEs from measurement data. We introduce a novel neural…

Numerical Analysis · Mathematics 2023-10-17 Ke Chen , Jasen Lai , Chunmei Wang

Partial Differential Equations (PDEs) are central to science and engineering. Since solving them is computationally expensive, a lot of effort has been put into approximating their solution operator via both traditional and recently…

Machine Learning · Computer Science 2025-02-14 Alessandro Longhi , Danny Lathouwers , Zoltán Perkó

This paper presents a safe output regulation control strategy for a class of systems modeled by a coupled $2\times 2$ hyperbolic PDE-ODE structure, subject to fully distributed disturbances throughout the system. A state-feedback controller…

Systems and Control · Electrical Eng. & Systems 2026-04-23 Ji Wang , Miroslav Krstic

A family of optimal control problems for a single and two coupled spinning particles in the Euler-Lagrange formalism is discussed. A characteristic of such problems is that the equations controlling the system are implicit and a reduction…

Optimization and Control · Mathematics 2016-01-20 M. Delgado-Téllez , A. Ibort , T. Rodríguez de la Peña , R. Salmoni

This paper is concerned with a linear quadratic optimal control for a class of singular Volterra integral equations. Under proper convexity conditions, optimal control uniquely exists, and it could be characterized via Frechet derivative of…

Optimization and Control · Mathematics 2021-09-17 Shuo Han , Ping Lin , Jiongmin Yong

This paper deals with the trajectory tracking control problem for a class of bilinear systems with unmeasurable states and unknown parameters. Firstly, a full-information controller is suggested that guarantees global tracking under a…

Systems and Control · Electrical Eng. & Systems 2023-09-06 Amir Reza Zare , Mahdi Aliyari shoorehdeli , Mehdi Tavan , Kamran Sabahi

The study of symmetries of partial differential equations (PDEs) has been traditionally treated as a geometrical problem. Although geometrical methods have been proven effective with regard to finding infinitesimal symmetry transformations,…

Analysis of PDEs · Mathematics 2025-11-03 C. J. Papachristou

In many scientific fields, the generation and evolution of data are governed by partial differential equations (PDEs) which are typically informed by established physical laws at the macroscopic level to describe general and predictable…

Methodology · Statistics 2025-07-01 Ziyuan Chen , Shunxing Yan , Fang Yao

Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC) is a well-established stabilization technique for affine nonlinear systems. However, its application is generally hindered by the requirement of solving a set of…

Optimization and Control · Mathematics 2026-01-06 Ziheng Jiao , Chengshuai Wu , Bo Fan , Meng Zhang , Romeo Ortega

We are interested in the numerical solution of coupled nonlinear partial differential equations (PDEs) in two and three dimensions. Under certain assumptions on the domain, we take advantage of the Kronecker structure arising in standard…

Numerical Analysis · Mathematics 2021-07-21 Gerhard Kirsten

Optimal control problems of forward stochastic Volterra integral equations (SVIEs) are formulated and studied. When control region is arbitrary subset of Euclidean space and control enters into the diffusion, necessary conditions of…

Optimization and Control · Mathematics 2018-02-06 Tianxiao Wang

We establish that stabilization of a class of linear, hyperbolic partial differential equations (PDEs) with a large (nevertheless finite) number of components, can be achieved via employment of a backstepping-based control law, which is…

Optimization and Control · Mathematics 2024-11-05 Jukka-Pekka Humaloja , Nikolaos Bekiaris-Liberis

Recent biological evidence suggests the presence of a two-phase ageing process in several species. We introduce a system of two age-structured partial differential equations (PDE) representing two phases of ageing of a wild population. The…

Analysis of PDEs · Mathematics 2026-03-24 Luce Breuil

This paper studies the linear-quadratic (LQ) optimal control problem of a class of systems governed by the first-order hyperbolic partial differential equations (PDEs) with final state constraints. The main contribution is to present the…

Optimization and Control · Mathematics 2024-11-25 Xiaomin Xue , Juanjuan Xu , Huanshui Zhang , Long Hu

We address the control of Partial Differential equations (PDEs) with unknown parameters. Our objective is to devise an efficient algorithm capable of both identifying and controlling the unknown system. We assume that the desired PDE is…

Optimization and Control · Mathematics 2024-02-14 Alessandro Alla , Agnese Pacifico

This study investigates a strongly-coupled system of partial differential equations (PDE) governing heat transfer in a copper rod, longitudinal vibrations, and total charge accumulation at electrodes within a magnetizable piezoelectric…

Optimization and Control · Mathematics 2024-03-14 Ahmet Ozkan Ozer , Ibrahim Khalilullah , Uthman Rasaq

While for coupled hyperbolic PDEs of first order there now exist numerous PDE backstepping designs, systems with zero speed, i.e., without convection but involving infinite-dimensional ODEs, which arise in many applications, from…

Optimization and Control · Mathematics 2022-11-28 Gustavo A. de Andrade , Rafael Vazquez , Iasson Karafyllis , Miroslav Krstic

This paper explores the difficulties in solving partial differential equations (PDEs) using physics-informed neural networks (PINNs). PINNs use physics as a regularization term in the objective function. However, a drawback of this approach…

Machine Learning · Computer Science 2023-06-21 Shamsulhaq Basir

Physics-informed neural networks (PINNs) have made significant strides in modeling dynamical systems governed by partial differential equations (PDEs). However, their generalization capabilities across varying scenarios remain limited. To…

Machine Learning · Computer Science 2024-12-02 Honghui Wang , Yifan Pu , Shiji Song , Gao Huang