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Stochastic economic dispatch models address uncertainties in forecasts of renewable generation output by considering a finite number of realizations drawn from a stochastic process model, typically via Monte Carlo sampling. Accurate…

Computational Engineering, Finance, and Science · Computer Science 2015-08-24 Cosmin Safta , Richard L. -Y. Chen , Habib N. Najm , Ali Pinar , Jean-Paul Watson

We revisit the problem of computing (robust) controlled invariant sets for discrete-time linear systems. Departing from previous approaches, we consider implicit, rather than explicit, representations for controlled invariant sets.…

Optimization and Control · Mathematics 2022-08-10 Tzanis Anevlavis , Zexiang Liu , Necmiye Ozay , Paulo Tabuada

Recently, a new family of integrators (Hamiltonian Boundary ValueMethods) has been introduced, which is able to precisely conserve the energy function of polynomial Hamiltonian systems and to provide a practical conservation of the energy…

Numerical Analysis · Mathematics 2010-10-19 Luigi Brugnano , Felice Iavernaro , Donato Trigiante

This paper investigates the second order asymptotic expansion for tail probabilities of discounted aggregate claims in continuous-time renewal risk models with constant interest force. Concretely, two types of continuous-time renewal risk…

Applications · Statistics 2025-01-07 Bingzhen Genga , Shijie Wanga , Yang Yang

We propose a homotopy continuation method called FLUX for approximating complicated probability density functions. It is based on progressive processing for smoothly morphing a given density into the desired one. Distributed ordinary…

Systems and Control · Computer Science 2018-08-09 Uwe D. Hanebeck

This paper introduces a novel method for the automatic detection and handling of nonlinearities in a generic transformation. A nonlinearity index that exploits second order Taylor expansions and polynomial bounding techniques is first…

Numerical Analysis · Mathematics 2024-02-05 Matteo Losacco , Alberto Fossà , Roberto Armellin

A new approach to design of nonlinear observers (state estimators) is proposed. The main idea is to (i) construct a convex set of dynamical systems which are contracting observers for a particular system, and (ii) optimize over this set for…

Systems and Control · Computer Science 2017-11-23 Ian R. Manchester

The state estimation of continuous-time nonlinear systems in which a subset of sensor outputs can be maliciously controlled through injecting a potentially unbounded additive signal is considered in this paper. Analogous to our earlier work…

Optimization and Control · Mathematics 2020-08-31 Michelle S. Chong , Henrik Sandberg , Joao P. Hespanha

In this paper, we propose a new approach to design globally convergent reduced-order observers for nonlinear control systems via contraction analysis and convex optimization. Despite the fact that contraction is a concept naturally suitable…

Optimization and Control · Mathematics 2021-08-17 Bowen Yi , Ruigang Wang , Ian R. Manchester

With the advancement of IoT technologies and the rapid expansion of cyber-physical systems, there is increasing interest in distributed state estimation, where multiple sensors collaboratively monitor large-scale dynamic systems. Compared…

Systems and Control · Electrical Eng. & Systems 2026-03-23 Ruixuan Zhao , Guitao Yang , James Fleming , Boli Chen

In this work, we investigate a model order reduction scheme for high-fidelity nonlinear structured parametric dynamical systems. More specifically, we consider a class of nonlinear dynamical systems whose nonlinear terms are polynomial…

Dynamical Systems · Mathematics 2023-01-24 Pawan Goyal , Igor Pontes Duff , Peter Benner

The limiting stability of invariant probability measures of time homogeneous transition semigroups for autonomous stochastic systems has been extensively discussed in the literature. In this paper we initially initiate a program to study…

Analysis of PDEs · Mathematics 2022-03-25 Renhai Wang , Tomas Caraballo , Nguyen Huy Tuan

General nonlinear continuous-time systems are considered for which its state is estimated via a packet-based communication network. We assume that the system has multiple sensor nodes, affected by measurement noise, which can transmit at…

Systems and Control · Electrical Eng. & Systems 2021-12-09 Koen J. A. Scheres , Michelle S. Chong , Romain Postoyan , W. P. Maurice H. Heemels

In this work we determine and discuss the entropic uncertainty measures of Shannon type for all the discrete stationary states of the multidimensional harmonic systems directly in terms of the states' hyperquantum numbers, the…

Quantum Physics · Physics 2018-12-19 I. V. Toranzo , J. S. Dehesa

A method of estimating the joint probability mass function of a pair of discrete random variables is described. This estimator is used to construct the conditional Shannon-R\'eyni-Tsallis entropies estimates. From there almost sure rates of…

Statistics Theory · Mathematics 2020-02-18 Ba Amadou Diadie , Lo Gane Samb

This paper is concerned with the problem of distributed estimation for time-varying interconnected dynamic systems with arbitrary coupling structures. To guarantee the robustness of the designed estimators, novel distributed stability…

Systems and Control · Electrical Eng. & Systems 2022-06-02 Yuchen Zhang , Bo Chen , Li Yu , Daniel W. C. Ho

This paper is aimed at extending the H-infinity Bounded Real Lemma to stochastic systems under random disturbances with imprecisely known probability distributions. The statistical uncertainty is measured in entropy theoretic terms using…

Systems and Control · Computer Science 2015-03-19 Michael M. Tchaikovsky , Alexander P. Kurdyukov , Victor N. Timin

Aerocapture is particularly challenging for semi-analytical propagation because the dynamics are dominated by nonconservative forces whose magnitudes vary significantly throughout the trajectory. State transition tensors (STTs),…

Systems and Control · Electrical Eng. & Systems 2026-05-26 Grace E. Calkins , Jay W. McMahon , David C. Woffinden

To construct flexible nonlinear predictive distributions, the paper introduces a family of softplus function based regression models that convolve, stack, or combine both operations by convolving countably infinite stacked gamma…

Machine Learning · Statistics 2016-08-24 Mingyuan Zhou

We define and study a new abstract domain which is a fine-grained combination of zonotopes with polyhedric domains such as the interval, octagon, linear templates or polyhedron domain. While abstract transfer functions are still rather…

Logic in Computer Science · Computer Science 2014-02-14 Khalil Ghorbal , Eric Goubault , Sylvie Putot