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A novel control design approach for general nonlinear systems is described in this paper. The approach is based on the identification of a polynomial model of the system to control and on the on-line inversion of this model. Extensive…

Systems and Control · Computer Science 2015-09-07 Carlo Novara

A common problem to all applications of linear finite dynamical systems is analyzing the dynamics without enumerating every possible state transition. Of particular interest is the long term dynamical behaviour. In this paper, we study the…

Dynamical Systems · Mathematics 2019-04-01 Björn Lindenberg

Dynamical systems with quadratic or polynomial drift exhibit complex dynamics, yet compared to nonlinear systems in general form, are often easier to analyze, simulate, control, and learn. Results going back over a century have shown that…

Symbolic Computation · Computer Science 2025-02-17 Boris Kramer , Gleb Pogudin

We develop a general framework for construction and analysis of discrete extension operators with application to unfitted finite element approximation of partial differential equations. In unfitted methods so called cut elements intersected…

Numerical Analysis · Mathematics 2021-01-26 Erik Burman , Peter Hansbo , Mats G. Larson

This paper focuses on the equidimensional decomposition of affine varieties defined by sparse polynomial systems. For generic systems with fixed supports, we give combinatorial conditions for the existence of positive dimensional components…

Algebraic Geometry · Mathematics 2012-11-16 Maria Isabel Herrero , Gabriela Jeronimo , Juan Sabia

This paper studies data-driven stabilization of a class of unknown polynomial systems using data corrupted by bounded noise. Existing work addressing this problem has focused on designing a controller and a Lyapunov function so that a…

Optimization and Control · Mathematics 2025-09-26 Huayuan Huang , M. Kanat Camlibel , Raffaella Carloni , Henk J. van Waarde

We revisit the analogy between feed-forward deep neural networks (DNNs) and discrete dynamical systems derived from neural integral equations and their corresponding partial differential equation (PDE) forms. A comparative analysis between…

Machine Learning · Computer Science 2026-05-21 Abhisek Ganguly , Santosh Ansumali , Sauro Succi

Practically all of the planning research is limited to states represented in terms of Boolean and numeric state variables. Many practical problems, for example, planning inside complex software systems, require far more complex data types,…

Artificial Intelligence · Computer Science 2023-01-02 Mojtaba Elahi , Jussi Rintanen

This paper deals with the computation of polytopic invariant sets for polynomial dynamical systems. An invariant set of a dynamical system is a subset of the state space such that if the state of the system belongs to the set at a given…

Optimization and Control · Mathematics 2015-03-17 Mohamed Amin Ben Sassi , Antoine Girard

Reverse derivative categories (RDCs) have recently been shown to be a suitable semantic framework for studying machine learning algorithms. Whereas emphasis has been put on training methodologies, less attention has been devoted to…

Machine Learning · Computer Science 2022-05-10 Paul Wilson , Fabio Zanasi

Mechanical and phononic metamaterials exhibiting negative elastic moduli, gapped vibrational spectra, or topologically protected modes enable precise control of structural and acoustic functionalities. While much progress has been made in…

Materials Science · Physics 2019-09-25 Henrik Ronellenfitsch , Norbert Stoop , Josephine Yu , Aden Forrow , Jörn Dunkel

When modeling scientific and industrial problems, geometries are typically modeled by explicit boundary representations obtained from computer-aided design software. Unfitted (also known as embedded or immersed) finite element methods offer…

Computational Engineering, Finance, and Science · Computer Science 2024-05-24 Pere A. Martorell , Santiago Badia

This paper presents an approach to model features and function nets of automotive systems comprehensively. In order to bridge the gap between feature requirements and function nets, we describe an approach to describe both using a…

Software Engineering · Computer Science 2014-09-24 Hans Grönninger , Jochen Hartmann , Holger Krahn , Stefan Kriebel , Bernhard Rumpe

Preliminary results of our investigations on solving indefinite qua\-dra\-tic programs by dynamical systems are given. First, dynamical systems corresponding to two fundamental DC programming algorithms to deal with indefinite quadratic…

Optimization and Control · Mathematics 2025-04-01 Massimo Pappalardo , Nguyen Nang Thieu , Nguyen Dong Yen

Integrating functions on discrete domains into neural networks is key to developing their capability to reason about discrete objects. But, discrete domains are (1) not naturally amenable to gradient-based optimization, and (2) incompatible…

Machine Learning · Computer Science 2022-11-15 Nikolaos Karalias , Joshua Robinson , Andreas Loukas , Stefanie Jegelka

We propose a unified framework for delay differential equations (DDEs) based on deep neural networks (DNNs) - the neural delay differential equations (NDDEs), aimed at solving the forward and inverse problems of delay differential…

Machine Learning · Computer Science 2024-08-27 Housen Wang , Yuxing Chen , Sirong Cao , Xiaoli Wang , Qiang Liu

Parameter estimation in structural dynamics generally involves inferring the values of physical, geometric, or even customized parameters based on first principles or expert knowledge, which is challenging for complex structural systems. In…

Computational Engineering, Finance, and Science · Computer Science 2025-04-08 Mingyuan Zhou , Haoze Song , Wenjing Ye , Wei Wang , Zhilu Lai

We introduce DDE-Solver, a Maple package designed for solving Discrete Differential Equations (DDEs). These equations are functional equations relating algebraically a formal power series F(t, u) with polynomial coefficients in a…

Combinatorics · Mathematics 2025-09-11 Hadrien Notarantonio

Nonlinear dynamics is a pervasive phenomenon observed in scientific and engineering disciplines. However, the task of deriving analytical expressions to describe nonlinear dynamics from limited data remains challenging. In this paper, we…

Machine Learning · Computer Science 2026-01-22 Zhongyi Jiang , Chunmei Wang , Haizhao Yang

This paper addresses problems on the structural design of control systems taking explicitly into consideration the possible application to large-scale systems. We provide an efficient and unified framework to solve the following major…

Optimization and Control · Mathematics 2014-09-23 Sergio Pequito , Soummya Kar , A. Pedro Aguiar