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We consider a networked control system (NCS) consisting of two plants, a global plant and a local plant, and two controllers, a global controller and a local controller. The global (resp. local) plant follows discrete-time stochastically…

Systems and Control · Computer Science 2018-02-05 Seyed Mohammad Asghari , Yi Ouyang , Ashutosh Nayyar

This paper presents a novel methodology to tackle feedback optimal control problems in scenarios where the exact state of the controlled process is unknown. It integrates data assimilation techniques and optimal control solvers to manage…

Optimization and Control · Mathematics 2024-04-10 Siming Liang , Ruoyu Hu , Feng Bao , Richard Archibald , Guannan Zhang

The paper describes a continuous second-variation algorithm to solve optimal control problems where the control is defined on a closed set. A second order expansion of a Lagrangian provides linear updates of the control to construct a…

Optimization and Control · Mathematics 2011-09-27 Joris T. Olympio

The synthesis of control laws for interacting agent-based dynamics and their mean-field limit is studied. A linearization-based approach is used for the computation of sub-optimal feedback laws obtained from the solution of differential…

Optimization and Control · Mathematics 2021-01-13 G. Albi , M. Herty , D. Kalise , C. Segala

In this paper, we study the social optimality for mean field linear quadratic control systems following the direct approach, where subsystems are coupled via individual dynamics and costs according to a network topology. A graph is…

Optimization and Control · Mathematics 2022-08-30 Yong Liang , Bingchang Wang , Huanshui Zhang

In this paper, we study representation formulas for finite-horizon optimal control problems with or without state constraints, unifying two different viewpoints: the Lagrangian and dynamic programming (DP) frameworks. In a recent work [1],…

Optimization and Control · Mathematics 2022-11-04 Yeoneung Kim , Insoon Yang

Distributed control problems under some specific information constraints can be formulated as (possibly infinite dimensional) convex optimization problems. The underlying motivation of this work is to develop an understanding of the optimal…

Optimization and Control · Mathematics 2014-03-19 Takashi Tanaka , Pablo A. Parrilo

In this paper we demonstrate how certain structured feedback gains necessarily emerge as the optimal controller gains in two linear optimal control formulations for multi-agent systems. We consider the cases of linear optimal…

Optimization and Control · Mathematics 2016-09-05 Shen Zeng , Frank Allgöwer

Online feedback optimization (OFO) enables optimal steady-state operations of a physical system by employing an iterative optimization algorithm as a dynamic feedback controller. When the plant consists of several interconnected…

Optimization and Control · Mathematics 2024-09-13 Wenbin Wang , Zhiyu He , Giuseppe Belgioioso , Saverio Bolognani , Florian Dörfler

Inspired and underpinned by the idea of integral feedback, a distributed constant gain algorithm is proposed for multi-agent networks to solve convex optimization problems with local linear constraints. Assuming agent interactions are…

Optimization and Control · Mathematics 2021-11-19 Xuan Wang , Shaoshuai Mou , Brian. D. O. Anderson

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…

Optimization and Control · Mathematics 2019-02-27 Mingshang Hu , Shaolin Ji , Xiaole Xue

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

In modern machine learning, models can often fit training data in numerous ways, some of which perform well on unseen (test) data, while others do not. Remarkably, in such cases gradient descent frequently exhibits an implicit bias that…

Machine Learning · Computer Science 2024-06-04 Noam Razin , Yotam Alexander , Edo Cohen-Karlik , Raja Giryes , Amir Globerson , Nadav Cohen

We propose an efficient algorithm for the optimal control problems (OCPs) of nonlinear switched systems that optimizes the control input and switching instants simultaneously for a given switching sequence. We consider the switching…

Optimization and Control · Mathematics 2021-06-09 Sotaro Katayama , Toshiyuki Ohtsuka

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…

Systems and Control · Electrical Eng. & Systems 2025-11-11 Sayak Mukherjee , Thanh Long Vu

Linearising the dynamics of nonlinear mechanical systems is an important and open research area. A common approach is feedback linearisation, which is a nonlinear control method that transforms the input-output response of a nonlinear…

Systems and Control · Electrical Eng. & Systems 2025-02-05 Merijn Floren , Koen Classens , Tom Oomen , Jean-Philippe Noël

We propose a new matrix pencil based approach for design of state-feedback and output-feedback stabilizing controllers for a general class of uncertain nonlinear strict-feedback-like systems. While the dynamic controller structure is based…

Optimization and Control · Mathematics 2022-06-08 Prashanth Krishnamurthy , Farshad Khorrami

The paper addresses the exact linearization of flat nonlinear discrete-time systems by generalized static or dynamic feedbacks which may also depend on forward-shifts of the new input. We first investigate the question which forward-shifts…

Optimization and Control · Mathematics 2022-12-29 Bernd Kolar , Johannes Diwold , Conrad Gstöttner , Markus Schöberl

We study in this paper the linear quadratic optimal control (linear quadratic regulation, LQR for short) for discrete-time complex-valued linear systems, which have shown to have several potential applications in control theory. Firstly, an…

Optimization and Control · Mathematics 2017-09-18 Bin Zhou

A new method is developed to deal with the problem that a complex decentralized control system needs to keep centralized control performance. The systematic procedure emphasizes quickly finding the decentralized subcontrollers that matching…

Systems and Control · Computer Science 2018-09-05 Ying Huang , Jiyang Dai , Chen Peng