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This paper introduces the notions of stability, ultimate boundedness, and positive invariance for stochastic systems in the view of risk. More specifically, those notions are defined in terms of the worst-case Conditional Value-at-Risk…

Optimization and Control · Mathematics 2023-08-29 Masako Kishida

We examine the minimization of a quadratic cost functional composed of the output and the final state of abstract infinite-dimensional evolution equations in view of existence of solutions and optimality conditions. While the initial value…

Optimization and Control · Mathematics 2024-12-20 Timo Reis , Manuel Schaller

We study here the impulse control minimax problem. We allow the cost functionals and dynamics to be unbounded and hence the value functions can possibly be unbounded. We prove that the value function of the problem is continuous. Moreover,…

Optimization and Control · Mathematics 2013-11-15 Brahim El Asri

Standard formulations of prescribed worst-case disturbance energy-gain control policies for linear time-varying systems depend on all forward model data. In discrete time, this dependence arises through a backward Riccati recursion. This…

Optimization and Control · Mathematics 2026-05-22 Jintao Sun , Michael Cantoni

The importance of feedback control is being increasingly appreciated in quantum physics and applications. This paper describes the use of optimal control methods in the design of quantum feedback control systems, and in particular the paper…

Quantum Physics · Physics 2009-11-10 M. R. James

A general backward stochastic linear-quadratic optimal control problem is studied, in which both the state equation and the cost functional contain the nonhomogeneous terms. The main feature of the problem is that the weighting matrices in…

Optimization and Control · Mathematics 2022-03-01 Jingrui Sun , Jiaqiang Wen , Jie Xiong

We consider a two-sided singular stochastic control problem with a risk-sensitive ergodic criterion. In particular, we consider a stochastic system whose uncontrolled dynamics are modelled by a linear diffusion. The control that can be…

Optimization and Control · Mathematics 2025-09-15 Justin Gwee , Mihail Zervos

We consider the problem of impulse control minimax in finite horizon, when cost functions $(C(t,x,\xi)>0)$. We show existence of value function of the problem. Moreover, the value function is characterized as the unique viscosity solution…

Optimization and Control · Mathematics 2013-05-07 Brahim El Asri

We consider the infinite horizon risk-sensitive problem for nondegenerate diffusions with a compact action space, and controlled through the drift. We only impose a structural assumption on the running cost function, namely…

Optimization and Control · Mathematics 2019-03-20 Ari Arapostathis , Anup Biswas

A general problem in optimal control consists of finding a terminal reward that makes the value function independent of the horizon. Such a terminal reward can be interpreted as a max-plus eigenvector of the associated Lax-Oleinik…

Optimization and Control · Mathematics 2007-12-05 Marianne Akian , Stephane Gaubert , Cormac Walsh

In this paper, a finite-horizon optimal control problem involving a dynamical system described by a linear Caputo fractional differential equation and a quadratic cost functional is considered. An explicit formula for the value functional…

Optimization and Control · Mathematics 2024-04-25 Mikhail I. Gomoyunov

We consider a liquidation problem in which a risk-averse trader tries to liquidate a fixed quantity of an asset in the presence of market impact and random price fluctuations. The trader encounters a trade-off between the transaction costs…

Trading and Market Microstructure · Quantitative Finance 2022-01-31 Seungki Min , Ciamac C. Moallemi , Costis Maglaras

In several real-world applications involving decision making under uncertainty, the traditional expected value objective may not be suitable, as it may be necessary to control losses in the case of a rare but extreme event. Conditional…

Machine Learning · Computer Science 2018-08-07 Ravi Kumar Kolla , Prashanth L. A. , Sanjay P. Bhat , Krishna Jagannathan

This paper is concerned with a discounted optimal control problem of partially observed forward-backward stochastic systems with jumps on infinite horizon. The control domain is convex and a kind of infinite horizon observation equation is…

Optimization and Control · Mathematics 2022-01-04 Yueyang Zheng , Jingtao Shi

In an equity market model with "Knightian" uncertainty regarding the relative risk and covariance structure of its assets, we characterize in several ways the highest return relative to the market that can be achieved using nonanticipative…

Probability · Mathematics 2012-02-15 Daniel Fernholz , Ioannis Karatzas

We introduce a numerically stable reformulation of controllability scoring based on a scaled controllability Gramian, which remains reliably computable even for unstable systems. The resulting optimization problems define dynamics-aware…

Optimization and Control · Mathematics 2026-01-21 Kota Umezu , Kazuhiro Sato

In this paper long-run risk sensitive optimisation problem is studied with dyadic impulse control applied to continuous-time Feller-Markov process. In contrast to the existing literature, focus is put on unbounded and non-uniformly ergodic…

Optimization and Control · Mathematics 2019-06-18 Marcin Pitera , Łukasz Stettner

We study a finite horizon optimal control problem for the continuity equation under a weighted integral state constraint on the mass outside a fixed set. The model is cast in a Hilbert framework for densities. On a suitable invariant…

Optimization and Control · Mathematics 2026-04-03 Fabio Bagagiolo , Ivan Romanò

We study the infinite-horizon distributionally robust (DR) control of linear systems with quadratic costs, where disturbances have unknown, possibly time-correlated distribution within a Wasserstein-2 ambiguity set. We aim to minimize the…

Optimization and Control · Mathematics 2024-06-12 Taylan Kargin , Joudi Hajar , Vikrant Malik , Babak Hassibi

The risk-neutral LQR controller is optimal for stochastic linear dynamical systems. However, the classical optimal controller performs inefficiently in the presence of low-probability yet statistically significant (risky) events. The…

Systems and Control · Electrical Eng. & Systems 2023-07-17 Masoud Roudneshin , Saba Sanami , Amir G. Aghdam