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This paper proposes a new framework and several results to quantify the performance of data-driven state-feedback controllers for linear systems against targeted perturbations of the training data. We focus on the case where subsets of the…

Systems and Control · Electrical Eng. & Systems 2019-12-24 Rajasekhar Anguluri , Abed AlRahman Al Makdah , Vaibhav Katewa , Fabio Pasqualetti

In this paper, we directly design a state feedback controller that stabilizes a class of uncertain nonlinear systems solely based on input-state data collected from a finite-length experiment. Necessary and sufficient conditions are derived…

Systems and Control · Electrical Eng. & Systems 2021-03-30 Alessandro Luppi , Claudio De Persis , Pietro Tesi

In this paper, a distributed output regulation problem is formulated for a class of uncertain nonlinear multi-agent systems subject to local disturbances. The formulation is given to study a leader-following problem when the leader contains…

Optimization and Control · Mathematics 2015-10-27 Yutao Tang , Yiguang Hong , Xinghu Wang

In order to address the nonlinear multi-agent formation tracking control problem with input constraints and unknown communication faults, a novel adaptive distributed observer-based distributed model predictive control method is developed…

Systems and Control · Electrical Eng. & Systems 2024-11-01 Binyan Xu , Yufan Dai , Afzal Suleman , Yang Shi

In this article, we consider a fundamental decentralized optimal control problem, which we call the two-player problem. Two subsystems are interconnected in a nested information pattern, and output feedback controllers must be designed for…

Systems and Control · Computer Science 2015-07-10 Laurent Lessard , Sanjay Lall

The model reduction problem for semistable infinite-dimensional control systems is studied in this paper. In relation to these systems, we study an object we call the semistability Gramian, which serves as a generalization of the ordinary…

Optimization and Control · Mathematics 2019-03-25 Ingvar Ziemann , Yishao Zhou

Advanced feedforward control methods enable mechatronic systems to perform varying motion tasks with extreme accuracy and throughput. The aim of this paper is to develop a data-driven feedforward controller that addresses input…

Systems and Control · Electrical Eng. & Systems 2023-11-30 Jilles van Hulst , Maurice Poot , Dragan Kostić , Kai Wa Yan , Jim Portegies , Tom Oomen

Parameter selection is one of the most important parts for nearly all the control strategies. Traditionally, controller parameters are chosen by utilizing trial and error, which is always tedious and time consuming. Moreover, such method is…

Systems and Control · Electrical Eng. & Systems 2022-04-13 Yujia Wang , Tong Wang , Jiae Yang , Xuebo Yang

In this paper, we address the problem of coordinating a set of distributed energy resources (DERs) to regulate voltage in power distribution systems to desired levels. To this end, we formulate the voltage control problem as an optimization…

Optimization and Control · Mathematics 2020-06-09 Hanchen Xu , Alejandro D. Domínguez-García , Peter W. Sauer

For many tasks, predictive path-following control can significantly improve the performance and robustness of autonomous robots over traditional trajectory tracking control. It does this by prioritizing closeness to the path over timed…

Robotics · Computer Science 2017-11-03 Melissa Greeff , Angela P. Schoellig

We develop a non-collocated, observer-based output-feedback law for a class of continua of linear hyperbolic PDE systems, which are viewed as the continuum version of $n+m$, general heterodirectional hyperbolic systems as $n\to\infty$. The…

Optimization and Control · Mathematics 2025-03-12 Jukka-Pekka Humaloja , Nikolaos Bekiaris-Liberis

This paper presents a controller design and optimization framework for nonlinear dynamic systems to track a given reference signal in the presence of disturbances when the task is repeated over a finite-time interval. This novel framework…

Systems and Control · Electrical Eng. & Systems 2023-04-04 Jiapeng Xu , Ying Tan , Xiang Chen

Distributed model predictive control (DMPC) is a flexible and scalable feedback control method applicable to a wide range of systems. While the stability analysis of DMPC is quite well understood, there exist only limited implementation…

Systems and Control · Electrical Eng. & Systems 2025-11-05 Gösta Stomberg , Henrik Ebel , Timm Faulwasser , Peter Eberhard

We introduce a class of distributed nonlinear control systems, termed as the flow-tracker dynamics, which capture phenomena where the average state is controlled by the average control input, with no individual agent has direct access to…

Optimization and Control · Mathematics 2022-11-09 Behrouz Touri , Bahman Gharesifard

This paper deals with the stabilization of a coupled system composed by an infinite-dimensional system and an ODE. Moreover, the control, which appears in the dynamics of the ODE, is subject to a general class of nonlinearities. Such a…

Analysis of PDEs · Mathematics 2021-04-09 Swann Marx , Lucas Brivadis , Daniele Astolfi

This paper addresses the distributed optimal frequency control of power systems considering a network-preserving model with nonlinear power flows and excitation voltage dynamics. Salient features of the proposed distributed control strategy…

Systems and Control · Computer Science 2018-02-14 Zhaojian Wang , Feng Liu , John Z. F. Pang , Steven Low , Shengwei Mei

We consider the problem of finding an input signal which transfers a linear boundary controlled 1D parabolic partial differential equation with spatially-varying coefficients from a given initial state to a desired final state. The initial…

Systems and Control · Electrical Eng. & Systems 2024-05-17 Soham Chatterjee , Vivek Natarajan

This paper investigates the stabilization of a coupled system comprising a parabolic PDE and an elliptic PDE with nonlinear terms. A rigorous backstepping design provides an explicit boundary control law and exponentially convergent…

Analysis of PDEs · Mathematics 2025-07-18 Kamal Fenza , Moussa Labbadi , Mohamed Ouzahra

Parameter control aims at realizing performance gains through a dynamic choice of the parameters which determine the behavior of the underlying optimization algorithm. In the context of evolutionary algorithms this research line has for a…

Neural and Evolutionary Computing · Computer Science 2020-11-10 Benjamin Doerr , Carola Doerr

Besides parametric uncertainties and disturbances, the unmodeled dynamics and time delay at the input are often present in practical systems, which cannot be ignored in some cases. This paper aims to solve output feedback tracking control…

Systems and Control · Computer Science 2020-03-10 Quan Quan , Hai Lin , Kai-Yuan Cai
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