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This paper is concerned with a kind of linear-quadratic (LQ) optimal control problem of backward stochastic differential equation (BSDE) with partial information. The cost functional includes cross terms between the state and control, and…

最优化与控制 · 数学 2025-09-03 Jialong Li , Zhiyong Yu , Wanying Yue

Control using quantized feedback is a fundamental approach to system synthesis with limited communication capacity. In this paper, we address the stabilization problem for unknown linear systems with logarithmically quantized feedback, via…

最优化与控制 · 数学 2022-03-11 Feiran Zhao , Xingchen Li , Keyou You

A finite horizon linear quadratic(LQ) optimal control problem is studied for a class of discrete-time linear fractional systems (LFSs) affected by multiplicative, independent random perturbations. Based on the dynamic programming technique,…

最优化与控制 · 数学 2016-07-01 J. J. Trujillo , V. M. Ungureanu

We consider a class of $\ell_0$-regularized linear-quadratic (LQ) optimal control problems. This class of problems is obtained by augmenting a penalizing sparsity measure to the cost objective of the standard linear-quadratic regulator…

最优化与控制 · 数学 2015-07-31 MirSaleh Bahavarnia

Understanding the optimization landscape of linear quadratic regulation (LQR) problems is fundamental to the design of efficient reinforcement learning solutions. Recent work has made significant progress in characterizing the landscape of…

系统与控制 · 电气工程与系统科学 2026-04-14 Jingliang Duan , Jie Li , Yinsong Ma , Liye Tang , Guofa Li , Liping Zhang , Shengbo Eben Li , Lin Zhao

We study unconstrained and constrained linear quadratic problems and investigate the suboptimality of the model predictive control (MPC) method applied to such problems. Considering MPC as an approximate scheme for solving the related fixed…

最优化与控制 · 数学 2023-06-06 Yuchao Li , Aren Karapetyan , John Lygeros , Karl H. Johansson , Jonas Mårtensson

In this paper, the optimal local and remote linear quadratic (LQ) control problem is studied for a networked control system (NCS) which consists of multiple subsystems and each of which is described by a general multiplicative noise…

最优化与控制 · 数学 2020-07-31 Qingyuan Qi , Lihua Xie , Huanshui Zhang

In this paper, the decentralized estimation and linear quadratic (LQ) control problem for a leader-follower networked system (LFNS) is studied from the perspective of asymmetric information. Specifically, for a leader-follower network, the…

最优化与控制 · 数学 2025-09-22 Yiting Luo , Wei Wang , Qingyuan Qi , Yang Liu , Jian Xu

The closed-loop stability and infinite-horizon performance of receding-horizon approximations are studied for non-stationary linear-quadratic regulator (LQR) problems. The approach is based on a lifted reformulation of the optimal control…

系统与控制 · 电气工程与系统科学 2023-09-06 Jintao Sun , Michael Cantoni

This paper is concerned with a general non-homogeneous stochastic linear quadratic (LQ) control problem with regime switching and random coefficients. We obtain the explicit optimal state feedback control and optimal value for this problem…

最优化与控制 · 数学 2023-07-17 Ying Hu , Xiaomin Shi , Zuo Quan Xu

We study the problem of designing a state feedback linear quadratic Gaussian (LQG) controller for a system in which the system matrices as well as the process noise covariance are unknown. We do a rigorous comparison between two approaches.…

系统与控制 · 电气工程与系统科学 2025-11-13 Mingxiang Liu , Damián Marelli , Minyue Fu , Qianqian Cai

Distributed optimal control is known to be challenging and can become intractable even for linear-quadratic regulator problems. In this work, we study a special class of such problems where distributed state feedback controllers can give…

系统与控制 · 电气工程与系统科学 2024-03-14 Johan Olsson , Runyu Zhang , Emma Tegling , Na Li

This paper delves into designing stabilizing feedback control gains for continuous linear systems with unknown state matrix, in which the control is subject to a general structural constraint. We bring forth the ideas from reinforcement…

系统与控制 · 电气工程与系统科学 2025-11-11 Sayak Mukherjee , Thanh Long Vu

Recently, there has been a surge in interest in safe and robust techniques within reinforcement learning (RL). Current notions of risk in RL fail to capture the potential for systemic failures such as abrupt stoppages from system failures…

系统与控制 · 计算机科学 2019-10-09 David Mguni

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…

最优化与控制 · 数学 2022-03-01 Jingrui Sun , Jiaqiang Wen , Jie Xiong

Synchronization control of coupled continuous-time linear systems is studied. For identical systems that are stabilizable, a linear feedback law obtained via algebraic Riccati equation is shown to synchronize any fixed directed network of…

最优化与控制 · 数学 2008-01-23 S. Emre Tuna

In networked control systems, often the sensory signals are quantized before being transmitted to the controller. Consequently, performance is affected by the coarseness of this quantization process. Modern communication technologies allow…

系统与控制 · 电气工程与系统科学 2021-11-09 Dipankar Maity , Panagiotis Tsiotras

The present paper develops an optimal linear quadratic boundary controller for $2\times2$ linear hyperbolic partial differential equations (PDEs) with actuation on only one end of the domain. First-order necessary conditions for optimality…

最优化与控制 · 数学 2016-03-30 Agus Hasan , Lars Imsland , Ivan Ivanov , Snezhana Kostova , Boryana Bogdanova

The optimal controller design problem for a linear, first-order spatially-invariant distributed parameter system is considered. Through a case study of the Linear Quadratic Regulator (LQR) problem for the diffusion equation over the torus,…

最优化与控制 · 数学 2026-03-20 Addie McCurdy , Andrew Gusty , Emily Jensen

Foundation models often generate unreliable answers, while heuristic uncertainty estimators fail to fully distinguish correct from incorrect outputs, causing users to accept erroneous answers without any statistical guarantee. We address…

人工智能 · 计算机科学 2026-05-27 Zhiyuan Wang , Aniri , Tianlong Chen , Yue Zhang , Heng Tao Shen , Xiaoshuang Shi , Kaidi Xu
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