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A control in feedback form is derived for linear quadratic, time-invariant optimal control problems subject to parabolic partial differential equations with coefficients depending on a countably infinite number of uncertain parameters. It…

Optimization and Control · Mathematics 2024-09-25 Philipp A. Guth , Peter Kritzer , Karl Kunisch

Accurate state estimates are required for increasingly complex systems, to enable, for example, feedback control. However, available state estimation schemes are not necessarily real-time feasible for certain large-scale systems. Therefore,…

Systems and Control · Electrical Eng. & Systems 2024-10-24 S. A. N. Nouwens , M. M. Paulides , W. P. M. H. Heemels

Markov chain Monte Carlo (MCMC) algorithms are indispensable when sampling from a complex, high-dimensional distribution by a conventional method is intractable. Even though MCMC is a powerful tool, it is also hard to control and tune in…

Graphics · Computer Science 2025-10-14 Sascha Holl , Gurprit Singh , Hans-Peter Seidel

In this technical note, we prove that the ODEFTC algorithm constitutes the first optimal distributed state estimator for continuous-time linear time-varying systems subject to stochastic disturbances. Particularly, we formally show that it…

Optimization and Control · Mathematics 2025-10-22 Irene Perez-Salesa , Rodrigo Aldana-Lopez , Carlos Sagues

Duality between estimation and optimal control is a problem of rich historical significance. The first duality principle appears in the seminal paper of Kalman-Bucy, where the problem of minimum variance estimation is shown to be dual to a…

Optimization and Control · Mathematics 2019-10-28 Jin W. Kim , Prashant G. Mehta , Sean P. Meyn

Real-world control applications often involve complex dynamics subject to abrupt changes or variations. Markov jump linear systems (MJS) provide a rich framework for modeling such dynamics. Despite an extensive history, theoretical…

Optimization and Control · Mathematics 2021-05-27 Zhe Du , Yahya Sattar , Davoud Ataee Tarzanagh , Laura Balzano , Samet Oymak , Necmiye Ozay

The theory of imprecise Markov chains has achieved significant progress in recent years. Its applicability, however, is still very much limited, due in large part to the lack of efficient computational methods for calculating…

Optimization and Control · Mathematics 2022-03-30 Damjan Škulj

We attempt to provide an algorithm for approximating a solution of the quasiconvex equilibrium problem that was proved to exist by K. Fan 1972. The proposed algorithm is an iterative procedure, where the search direction at each iteration…

Optimization and Control · Mathematics 2023-04-25 Le Hai Yen , Le Dung Muu

Time-continuous non-anticipating quantum processes of nondemolition measurements are introduced as the dynamical realizations of the causal quasi-measurements, which are described in this paper by the adapted operator-valued probability…

Quantum Physics · Physics 2007-05-23 V. P. Belavkin

System level synthesis enables improved robust MPC formulations by allowing for joint optimization of the nominal trajectory and controller. This paper introduces a tailored algorithm for solving the corresponding disturbance feedback…

Optimization and Control · Mathematics 2024-09-05 Antoine P. Leeman , Johannes Köhler , Florian Messerer , Amon Lahr , Moritz Diehl , Melanie N. Zeilinger

Fluid approximations have seen great success in approximating the macro-scale behaviour of Markov systems with a large number of discrete states. However, these methods rely on the continuous-time Markov chain (CTMC) having a particular…

Systems and Control · Electrical Eng. & Systems 2019-10-29 Michalis Michaelides , Jane Hillston , Guido Sanguinetti

This paper investigates a linear quadratic stochastic optimal control (LQSOC) problem with partial information. Firstly, by introducing two Riccati equations and a backward stochastic differential equation (BSDE), we solve this LQSOC…

Optimization and Control · Mathematics 2024-09-26 Xun Li , Guangchen Wang , Jie Xiong , Heng Zhang

This paper introduces time-continuous numerical schemes to simulate stochastic differential equations (SDEs) arising in mathematical finance, population dynamics, chemical kinetics, epidemiology, biophysics, and polymeric fluids. These…

Probability · Mathematics 2015-03-13 Nawaf Bou-Rabee , Eric Vanden-Eijnden

In this paper, we study the quasi-potential for a general class of damped semilinear stochastic wave equations. We show that, as the density of the mass converges to zero, the infimum of the quasi-potential with respect to all possible…

Probability · Mathematics 2014-03-25 Sandra Cerrai , Michael Salins

This paper deals with the finite horizon optimal control problem for discrete-time Markov jump linear system with input delay. The correlation among the jumping parameters and the input delay are considered simultaneously, which forms the…

Optimization and Control · Mathematics 2018-08-22 Chunyan Han , Hongdan Li , Huanshui Zhang

We address the problem of the best uniform approximation by linear combinations of a finite system of functions. If the system is Chebyshev and the problem is unconstrained, then the classical Remez algorithm provides a fast and precise…

Numerical Analysis · Mathematics 2025-07-08 Vladimir Yu. Protasov , Rinat Kamalov

This paper investigates the stability of Kalman filtering over Gilbert-Elliott channels where random packet drop follows a time-homogeneous two-state Markov chain whose state transition is determined by a pair of failure and recovery rates.…

Systems and Control · Computer Science 2014-11-06 Junfeng Wu , Guodong Shi , Brian D. O. Anderson , Karl Henrik Johansson

Recent quasi-optimal error estimates for the finite element approximation of total-variation regularized minimization problems using the Crouzeix--Raviart finite element require the existence of a Lipschitz continuous dual solution, which…

Numerical Analysis · Mathematics 2022-01-12 Alex Kaltenbach , Sören Bartels

In this article, we introduce decentralized Kalman filters for linear quadratic deep structured teams. The agents in deep structured teams are coupled in dynamics, costs and measurements through a set of linear regressions of the states and…

Multiagent Systems · Computer Science 2021-10-26 Jalal Arabneydi , Amir G. Aghdam

Computational fluid dynamics (CFD) is a cornerstone of classical scientific computing, and there is growing interest in whether quantum computers can accelerate such simulations. To date, the existing proposals for fault-tolerant quantum…