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In this paper, we consider a linear-quadratic optimal control problem of mean-field stochastic differential equation with jump diffusion, which is also called as an MF-LQJ problem. Here, cost functional is allowed to be indefinite. We use…

Optimization and Control · Mathematics 2021-11-18 Guangchen Wang , Wencan Wang

Linear-quadratic Gaussian games provide a framework for modeling strategic interactions in multi-agent systems, where agents must estimate system states from noisy observations while also making decisions to optimize a quadratic cost.…

Systems and Control · Electrical Eng. & Systems 2026-03-19 Tianyu Qiu , Filippos Fotiadis , Xinjie Liu , Christian Ellis , Jesse Milzman , Wesley Suttle , Ufuk Topcu , David Fridovich-Keil

This paper studies asymptotic solvability of a linear quadratic (LQ) mean field social optimization problem with controlled diffusions and indefinite state and control weights. Starting with an $N$-agent model, we employ a rescaling…

Optimization and Control · Mathematics 2021-09-14 Minyi Huang , Xuwei Yang

In this paper, we study non-homogeneous stochastic linear-quadratic (LQ) optimal control problems with multi-dimensional state and regime switching. We focus on the corresponding stochastic Riccati equation, which is the same as that one in…

Optimization and Control · Mathematics 2024-04-02 Yuyang Chen , Peng Luo

This paper addresses the problem of collaborative formation control for multi-agent systems with limited resources. We consider a team of robots tasked with achieving a desired formation from an arbitrary initial configuration. To reduce…

Robotics · Computer Science 2026-04-07 Evangelos Psomiadis , Panagiotis Tsiotras

This paper investigates a class of unified stochastic linear quadratic Gaussian (LQG) social optima problems involving a large number of weakly-coupled interactive agents under a {generalized} setting. For each individual agent, the control…

Optimization and Control · Mathematics 2020-05-15 Zhenghong Qiu , Jianhui Huang , Tinghan Xie

This paper studies the linear quadratic regulation (LQR) problem of unknown discrete-time systems via dynamic output feedback learning control. In contrast to the state feedback, the optimality of the dynamic output feedback control for…

Systems and Control · Electrical Eng. & Systems 2025-05-29 Kedi Xie , Martin Guay , Shimin Wang , Fang Deng , Maobin Lu

This paper presents a novel data-driven approach for approximating the $\varepsilon$-Nash equilibrium in continuous-time linear quadratic Gaussian (LQG) games, where multiple agents interact with each other through their dynamics and…

Systems and Control · Electrical Eng. & Systems 2025-07-22 Zhenhui Xu , Jiayu Chen , Bing-Chang Wang , Tielong Shen

We consider transport processes that are modeled by first order hyperbolic partial differential equations. Our goal is to find a full state feedback that makes a given reference profile locally asymptotically stable. To accomplish this we…

Optimization and Control · Mathematics 2025-08-22 Arthur J. Krener

In this paper, we formulate a general time-inconsistent stochastic linear--quadratic (LQ) control problem. The time-inconsistency arises from the presence of a quadratic term of the expected state as well as a state-dependent term in the…

Optimization and Control · Mathematics 2011-11-04 Ying Hu , Hanqing Jin , Xun Yu Zhou

In this paper, we consider a linear quadratic stochastic two-person nonzero-sum differential game. Open-loop and closed-loop Nash equilibria are introduced. The existence of the former is characterized by the solvability of a system of…

Optimization and Control · Mathematics 2016-07-18 Jingrui Sun , Jiongmin Yong

We propose a computational framework for replacing the repeated numerical solution of differential Riccati equations in finite-horizon Linear Quadratic Regulator (LQR) problems by a learned operator surrogate. Instead of solving a nonlinear…

Optimization and Control · Mathematics 2026-04-22 Jun Chen , Umberto Biccari , Junmin Wang

This paper is concerned with linear quadratic optimal control problems for mean-field backward stochastic differential equations (MF-BSDEs, for short) with deterministic coefficients. The optimality system, which is a linear mean-field…

Optimization and Control · Mathematics 2016-10-11 Xun Li , Jingrui Sun , Jie Xiong

We consider a class of stochastic control problems with a delayed control, both in drift and diffusion, of the type dX t = $\alpha$ t--d (bdt + $\sigma$dW t). We provide a new characterization of the solution in terms of a set of Riccati…

Optimization and Control · Mathematics 2021-02-25 William Lefebvre , Enzo Miller

This paper presents a sample-efficient, data-driven control framework for finite-horizon linear quadratic (LQ) control of linear time-varying (LTV) systems. In contrast to the time-invariant case, the time-varying LQ problem involves a…

Systems and Control · Electrical Eng. & Systems 2025-09-30 Sahel Vahedi Noori , Maryam Babazadeh

We derive an explicit solution to the operator Riccati equation solving the Linear-Quadratic (LQ) optimal control problem for a class of boundary controlled hyperbolic partial differential equations (PDEs). Different descriptions of the…

Optimization and Control · Mathematics 2025-03-17 Anthony Hastir , Birgit Jacob , Hans Zwart

In this paper, we address the inverse problem for linear-quadratic differential non-cooperative games with output-feedback. Given players' stabilizing feedback laws, the goal is to find cost function parameters that lead to a game for which…

Optimization and Control · Mathematics 2024-10-27 Emin Martirosyan , Ming Cao

We consider the linear quadratic Gaussian control problem with a discounted cost functional for descriptor systems on the infinite time horizon. Based on recent results from the deterministic framework, we characterize the feasibility of…

Optimization and Control · Mathematics 2020-04-21 Hermann Mena , Lena-Maria Pfurtscheller , Matthias Voigt

In this paper, we consider the adaptive linear quadratic Gaussian control problem, where both the linear transformation matrix of the state $A$ and the control gain matrix $B$ are unknown. The proposed adaptive optimal control only assumes…

Optimization and Control · Mathematics 2024-09-17 Nian Liu , Cheng Zhao , Shaolin Tan , Jinhu Lü

Dynamic game arises as a powerful paradigm for multi-robot planning, for which safety constraint satisfaction is crucial. Constrained stochastic games are of particular interest, as real-world robots need to operate and satisfy constraints…

Robotics · Computer Science 2026-03-27 Hai Zhong , Yutaka Shimizu , Jianyu Chen
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