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相关论文: Two-Timescale Optimization Framework for Sparse-Fe…

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We consider the problem of output feedback controller sparsification for systems with parametric uncertainties. We develop an optimization scheme that minimizes the performance deterioration caused by the sparsification process, while…

最优化与控制 · 数学 2018-05-16 Reza Arastoo , MirSaleh Bahavarnia

We study the distributed Linear Quadratic Gaussian (LQG) control problem in discrete-time and finite-horizon, where the controller depends linearly on the history of the outputs and it is required to lie in a given subspace, e.g. to possess…

系统与控制 · 电气工程与系统科学 2021-07-14 Luca Furieri , Maryam Kamgarpour

Tools from control and dynamical systems have proven valuable for analyzing and developing optimization methods. In this paper, we establish rigorous theoretical foundations for using feedback linearization (FL) -- a well-established…

最优化与控制 · 数学 2026-01-29 Runyu Zhang , Arvind Raghunathan , Jeff Shamma , Na Li

This paper first presents necessary and sufficient conditions for the solvability of discrete time, mean-field, stochastic linear-quadratic optimal control problems. Then, by introducing several sequences of bounded linear operators, the…

最优化与控制 · 数学 2016-07-25 Robert. J Elliott , Xun Li , Yuan-Hua Ni

This paper introduces a generalization of the well-known Riccati recursion for solving the discrete-time equality-constrained linear quadratic optimal control problem. The recursion can be used to compute the solutions as well as optimal…

最优化与控制 · 数学 2024-12-31 Lander Vanroye , Joris De Schutter , Wilm Decré

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…

系统与控制 · 电气工程与系统科学 2025-09-30 Sahel Vahedi Noori , Maryam Babazadeh

Recent developments in cyber-physical systems and event-triggered control have led to an increased interest in the impact of sparse disturbances on dynamical processes. We study Linear Quadratic Regulator (LQR) control under sparse…

系统与控制 · 电气工程与系统科学 2022-09-23 Samuel Pfrommer , Somayeh Sojoudi

Linear-quadratic regulator (LQR) is a landmark problem in the field of optimal control, which is the concern of this paper. Generally, LQR is classified into state-feedback LQR (SLQR) and output-feedback LQR (OLQR) based on whether the full…

最优化与控制 · 数学 2024-04-16 Lechen Feng , Yuan-Hua Ni

This paper focuses on the discrete-time backward stochastic linear quadratic (BSLQ) optimal control problem with nonhomogeneous system terms and cost function cross terms. The terminal constraint of such systems distinguishes it from…

最优化与控制 · 数学 2026-04-14 Hu Ligui , Meng Qingxin , Tang Maoning

In this paper we present and analyze a weighted residual a posteriori error estimate for an optimal control problem. The problem involves a nondifferentiable cost functional, a state equation with an integral fractional Laplacian, and…

数值分析 · 数学 2023-09-18 Fangyuan Wang , Qiming Wang , Zhaojie Zhou

In this paper we address the problem of information-constrained optimal control for an interconnected system subject to one-step communication delays and power constraints. The goal is to minimize a finite-horizon quadratic cost by…

系统与控制 · 计算机科学 2018-03-21 V. Causevic , P. Ugo Abara , S. Hirche

We consider the problem of optimal sparse output feedback controller synthesis for continuous linear time invariant systems when the feedback gain is static and subject to specified structural constraints. Introducing an additional term…

最优化与控制 · 数学 2015-06-23 Reza Arastoo , Nader Motee , Mayuresh V. Kothare

The convergence of policy gradient algorithms in reinforcement learning hinges on the optimization landscape of the underlying optimal control problem. Theoretical insights into these algorithms can often be acquired from analyzing those of…

机器学习 · 计算机科学 2023-11-01 Jingliang Duan , Wenhan Cao , Yang Zheng , Lin Zhao

A method is presented for solving the discrete-time finite-horizon Linear Quadratic Regulator (LQR) problem subject to auxiliary linear equality constraints, such as fixed end-point constraints. The method explicitly determines an affine…

系统与控制 · 计算机科学 2018-09-18 Forrest Laine , Claire Tomlin

A study of the linear quadratic (LQ) control problem on a finite time interval for a model equation in Hilbert spaces which comprehends the memory of the inputs was performed recently by the authors. The outcome included a closed-loop…

最优化与控制 · 数学 2025-03-19 Paolo Acquistapace , Francesca Bucci

In the past couple of decades, non-quadratic convex penalties have reshaped signal processing and machine learning; in robust control, however, general convex costs break the Riccati and storage function structure that make the design…

系统与控制 · 电气工程与系统科学 2025-08-21 Joudi Hajar , Reza Ghane , Babak Hassibi

In this paper, we introduce three QUBO (Quadratic Unconstrained Binary Optimization) relaxations for the sparsest $k$-subgraph (SkS) problem: a quadratic penalty relaxation, a Lagrangian relaxation, and an augmented Lagrangian relaxation.…

最优化与控制 · 数学 2025-09-11 Omkar Bihani , Roman Kužel , Janez Povh , Dunja Pucher

This paper develops a controller synthesis algorithm for distributed LQG control problems under output feedback. We consider a system consisting of three interconnected linear subsystems with a delayed information sharing structure. While…

系统与控制 · 计算机科学 2016-11-15 Hamid Reza Feyzmahdavian , Assad Alam , Ather Gattami

Linear Quadratic Regulator (LQR) design is one of the most classical optimal control problems, whose well-known solution is an input sequence expressed as a state-feedback. In this work, finite-horizon and discrete-time LQR is solved under…

最优化与控制 · 数学 2020-01-17 Anna Scampicchio , Aleksandr Aravkin , Gianluigi Pillonetto

This paper is concerned with optimal control of stochastic fully coupled forward-backward linear quadratic (FBLQ) problems with indefinite control weight costs. In order to obtain the state feedback representation of the optimal control, we…

最优化与控制 · 数学 2019-02-27 Mingshang Hu , Shaolin Ji , Xiaole Xue