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The data-driven discovery of interpretable models approximating the underlying dynamics of a physical system has gained attraction in the past decade. Current approaches employ pre-specified functional forms or basis functions and often…

Machine Learning · Computer Science 2025-07-30 Rahul Golder , M. M. Faruque Hasan

Solutions to most nonlinear ordinary differential equations (ODEs) rely on numerical solvers, but this gives little insight into the nature of the trajectories and is relatively expensive to compute. In this paper, we derive analytic…

Dynamical Systems · Mathematics 2024-06-25 Estelle Basor , Rebecca Morrison

Ordinary differential equations (ODEs) provide a powerful framework for modeling dynamic systems arising in a wide range of scientific domains. However, most existing ODE methods focus on a single system, and do not adequately address the…

Methodology · Statistics 2026-04-08 Shuoxun Xu , Zijian Guo , Brooke R. Staveland , Robert T. Knight , Lexin Li

A version of the Dynamical Systems Method for solving ill-posed nonlinear equations with monotone and locally H\"{o}lder continuous operators is studied in this paper. A discrepancy principle is proposed and justified under natural and weak…

Dynamical Systems · Mathematics 2010-03-29 N. S. Hoang

We introduce methods for deriving analytic solutions from differential-algebraic systems of equations (DAEs), as well as methods for deriving governing equations for analytic characterization which is currently limited to very small systems…

General Mathematics · Mathematics 2021-02-05 Samiya A Alkhairy

We develop a novel multi-layer predictor-feedback to achieve exact compensation of state-dependent input delay of general nonlinear integro-differential equations. The system of interest is an unconventional mixed Partial Differential…

Optimization and Control · Mathematics 2026-04-09 Tong Li , Peipei Shang , Mamadou Diagne

A high-order finite element method is proposed to solve the nonlinear convection-diffusion equation on a time-varying domain whose boundary is implicitly driven by the solution of the equation. The method is semi-implicit in the sense that…

Numerical Analysis · Mathematics 2022-01-03 Chuwen Ma , Weiying Zheng

We introduce a high-order numerical scheme for fractional ordinary differential equations with the Caputo derivative. The method is developed by dividing the domain into a number of subintervals, and applying the quadratic interpolation on…

Numerical Analysis · Mathematics 2020-02-25 Junying Cao , Zhenning Cai

Moment estimation for stochastic differential equations (SDEs) is fundamental to the formal reasoning and verification of stochastic dynamical systems, yet remains challenging and is rarely available in closed form. In this paper, we study…

Systems and Control · Electrical Eng. & Systems 2026-03-04 Shenghua Feng , Jie An , Naijun Zhan , Fanjiang Xu

We develop an efficient $hp$-finite element method for piecewise-smooth differential equations with periodic boundary conditions, using orthogonal polynomials defined on circular arcs. The operators derived from this basis are banded and…

Numerical Analysis · Mathematics 2025-12-23 Daniel VandenHeuvel , Sheehan Olver

Dynamic power system models are instrumental in real-time stability, monitoring, and control. Such models are traditionally posed as systems of nonlinear differential algebraic equations (DAEs): the dynamical part models generator…

Systems and Control · Electrical Eng. & Systems 2024-02-02 Mohamad H. Kazma , Ahmad F. Taha

Ordinary differential equations (ODEs) are a mathematical model used in many application areas such as climatology, bioinformatics, and chemical engineering with its intuitive appeal to modeling. Despite ODE's wide usage in modeling, the…

Applications · Statistics 2021-08-10 Hyunjoo Yang , Jaeyong Lee

In engineering, accurately modeling nonlinear dynamic systems from data contaminated by noise is both essential and complex. Established Sequential Monte Carlo (SMC) methods, used for the Bayesian identification of these systems, facilitate…

Machine Learning · Statistics 2024-04-25 Joe D. Longbottom , Max D. Champneys , Timothy J. Rogers

Exponential time differencing methods is a power tool for high-performance numerical simulation of computationally challenging problems in condensed matter physics, fluid dynamics, chemical and biological physics, where mathematical models…

Numerical Analysis · Mathematics 2024-10-15 Evelina V. Permyakova , Denis S. Goldobin

This paper proposes a frequency/time hybrid integral-equation method for the time dependent wave equation in two and three-dimensional spatial domains. Relying on Fourier Transformation in time, the method utilizes a fixed…

Numerical Analysis · Mathematics 2020-04-30 Thomas G. Anderson , Oscar P. Bruno , Mark Lyon

In this study, we propose high-order implicit and semi-implicit schemes for solving ordinary differential equations (ODEs) based on Taylor series expansion. These methods are designed to handle stiff and non-stiff components within a…

Numerical Analysis · Mathematics 2024-09-19 S. Boscarino , E. Macca

The increasing penetration of renewable energy sources, characterised by low inertia and intermittent disturbances, presents substantial challenges to power system stability. As critical indicators of system stability, frequency dynamics…

Systems and Control · Electrical Eng. & Systems 2025-02-19 Xiao Li , Xinyi Wen , Benjamin Schäfer

The harmonic balance method is the most commonly used method for solving periodic solutions of nonlinear dynamic systems, but the high-order approximation of nonlinear terms requires sophisticated formula derivation, which limits its…

Numerical Analysis · Mathematics 2023-08-02 Dai Honghua , Wang Qisi , Yan Zipu , Yue Xiaokui

We propose a methodology to address two analysis problems concerning complex systems, namely bounding state functionals of stochastic differential equations (SDEs) and verifying set avoidance of systems described by partial differential…

Optimization and Control · Mathematics 2016-03-30 Mohamadreza Ahmadi , Giorgio Valmorbida , Antonis Papachristodoulou

We consider a nonlinear ordinary differential equation and want to control its behavior so that it reaches a target by minimizing a cost function. Our approach is to use hybrid systems to solve this problem: the complex dynamic is replaced…

Optimization and Control · Mathematics 2008-01-07 Jean-Guillaume Luc Dumas , Aude Rondepierre