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Related papers: Reconfigurable Timed Discrete-Event Systems

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The existing Neural ODE formulation relies on an explicit knowledge of the termination time. We extend Neural ODEs to implicitly defined termination criteria modeled by neural event functions, which can be chained together and…

Machine Learning · Computer Science 2021-10-28 Ricky T. Q. Chen , Brandon Amos , Maximilian Nickel

In this paper we study the fault codiagnosis problem for discrete event systems given by finite automata (FA) and timed systems given by timed automata (TA). We provide a uniform characterization of codiagnosability for FA and TA which…

Formal Languages and Automata Theory · Computer Science 2010-04-16 Franck Cassez

In this article, we investigate both forward and backward problems for coupled systems of time-fractional diffusion equations, encompassing scenarios of strong coupling. For the forward problem, we establish the well-posedness of the…

Analysis of PDEs · Mathematics 2025-08-19 Dian Feng , Yikan Liu , Shuai Lu

By analogy with the theory of Backward Stochastic Differential Equations, we define Backward Stochastic Difference Equations on spaces related to discrete time, finite state processes. This paper considers these processes as constructions…

Probability · Mathematics 2010-07-12 Samuel N. Cohen , Robert J. Elliott

Event-triggered and self-triggered control have recently been proposed as implementation strategies that considerably reduce the resources required for control. Although most of the work so far has focused on closing a single control loop,…

Optimization and Control · Mathematics 2011-09-05 Romain Postoyan , Paulo Tabuada , Dragan Nesic , Adolfo Anta

In this paper, we consider an inverse space-dependent source problem for a time-fractional diffusion equation. To deal with the ill-posedness of the problem, we transform the problem into an optimal control problem with total variational…

Optimization and Control · Mathematics 2025-01-15 Bin Fan

Consider a discrete-time linear time-invariant descriptor system $Ex(k+1)=Ax(k)$ for $k \in \mathbb Z_{+}$. In this paper, we tackle for the first time the problem of stabilizing such systems by computing a nearby regular index one stable…

Optimization and Control · Mathematics 2019-10-11 Nicolas Gillis , Michael Karow , Punit Sharma

This paper considers differential problems with random switching, with specific applications to the motion of cells and centrally coordinated motion. Starting with a differential-equation model of cell motion that was proposed previously,…

This paper studies distributed resilient consensus problem for a class of uncertain nonlinear multiagent systems susceptible to deception attacks. The attacks invade both sensor and actuator channels of each agent. A specific class of…

Systems and Control · Electrical Eng. & Systems 2025-06-10 Mengze Yu , Wei Wang , Jiaqi Yan

Stochastic choice-based discrete planning is a broad class of decision-making problems characterized by a sequential decision-making process involving a planner and a group of customers. The firm or planner first decides a subset of options…

Optimization and Control · Mathematics 2024-09-20 Jiajie Zhang , Yun Hui Lin , Gerardo Berbeglia

We discuss the identification of a time-dependent potential in a time-fractional diffusion model from a boundary measurement taken at a single point. Theoretically, we establish a conditional Lipschitz stability for this inverse problem.…

Numerical Analysis · Mathematics 2024-07-23 Siyu Cen , Kwancheol Shin , Zhi Zhou

This paper studies the distributed optimization problem with possibly nonidentical local constraints, where its global objective function is composed of $N$ convex functions. The aim is to solve the considered optimization problem in a…

Optimization and Control · Mathematics 2022-08-26 Hongzhe Liu , Wenwu Yu , Guanghui Wen , Wei Xing Zheng

This paper considers the problem of controlling a piecewise continuously differentiable system subject to time-varying uncertainties. The uncertainties are decomposed into a time-invariant, linearly-parameterized portion and a time-varying…

Systems and Control · Electrical Eng. & Systems 2025-03-12 Ying-Chun Chen , Craig Woolsey

We study the use of Temporal-Difference learning for estimating the structural parameters in dynamic discrete choice models. Our algorithms are based on the conditional choice probability approach but use functional approximations to…

Econometrics · Economics 2022-12-23 Karun Adusumilli , Dita Eckardt

We consider the Chance Constrained Model Predictive Control problem for polynomial systems subject to disturbances. In this problem, we aim at finding optimal control input for given disturbed dynamical system to minimize a given cost…

Optimization and Control · Mathematics 2016-05-04 Ashkan Jasour , Constantino Lagoa

In earlier work we have studied a method for discretization in time of a parabolic problem which consists in representing the exact solution as an integral in the complex plane and then applying a quadrature formula to this integral. In…

Numerical Analysis · Mathematics 2016-02-02 William McLean , Vidar Thomée

We consider the model reduction problem for linear time-invariant dynamical systems having nonzero (but otherwise indeterminate) initial conditions. Building upon the observation that the full system response is decomposable as a…

Systems and Control · Computer Science 2017-01-04 Christopher A. Beattie , Serkan Gugercin , Volker Mehrmann

This paper studies an optimal ON-OFF control problem for a class of discrete event systems with real-time constraints. Our goal is to minimize the overall costs, including the operating cost and the wake-up cost, while still guaranteeing…

Optimization and Control · Mathematics 2018-09-07 Lei Miao , Lijian Xu , Dingde Jiang

This work unifies pseudo-time and inexact regularization techniques for nonmonotone classes of partial differential equations, into a regularized pseudo-time framework. Convergence of the residual at the predicted rate is investigated…

Numerical Analysis · Mathematics 2016-11-29 Sara Pollock

This paper proposes a method for modeling event sequences with ambiguous timestamps, a time-discounting convolution. Unlike in ordinary time series, time intervals are not constant, small time-shifts have no significant effect, and…

Machine Learning · Computer Science 2018-12-07 Takayuki Katsuki , Takayuki Osogami , Akira Koseki , Masaki Ono , Michiharu Kudo , Masaki Makino , Atsushi Suzuki