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We construct structured H-Infinity optimal model matching problems with rational coefficients, in which the optimal solution is not rational, in the sense that the cost does not achieve its maximal lower bound on the set of rational…

Optimization and Control · Mathematics 2013-05-28 Alexandre Megretski

Infinite-dimensional linear systems with unbounded input and output operators are considered. For the purpose of finite-dimensional observer-based state feedback, an observer approximation scheme will be developed which can be directly…

Optimization and Control · Mathematics 2022-11-28 Marcus Riesmeier , Frank Woittennek

This paper investigates the $H_{2}/H_{\infty}$ control problem for linear stochastic differential systems under partial observation. Unlike existing studies that assume full state accessibility, we consider the scenario where the controller…

Optimization and Control · Mathematics 2026-04-24 Changwang Xiao , Nan Yang , Qingxin Meng

Output reference tracking of unknown nonlinear systems is considered. The control objective is exact tracking in predefined finite time, while in the transient phase the tracking error evolves within a prescribed boundary. To achieve this,…

Optimization and Control · Mathematics 2024-08-29 Lukas Lanza

This paper is concerned with the optimal control of hysteresis-reaction-diffusion systems. We study a control problem with two sorts of controls, namely distributed control functions, or controls which act on a part of the boundary of the…

Optimization and Control · Mathematics 2017-06-01 Christian Münch

In this paper, we prove the exponential stabilization of solutions for complex Ginzburg-Landau equations using finite-parameter feedback control algorithms, which employ finitely many volume elements, Fourier modes or nodal observables…

Optimization and Control · Mathematics 2017-05-15 Jamila Kalantarova , Türker Özsarı

We here consider optimal control problems governed by nonlinear stochastic equations on a Hilbert space H with nonconvex payoff, which is rewritten as a deterministic optimal control problem governed by a Kolmogorov equation in H. We prove…

Probability · Mathematics 2019-12-16 Viorel Barbu , Michael Röckner , Deng Zhang

In this note we consider a class of linear time invariant systems with infinitely many unstable modes. By using the parameterization of all stabilizing controllers and a data transformation, we show that H-infinity controllers for such…

Systems and Control · Electrical Eng. & Systems 2020-03-13 Suat Gumussoy , Hitay Ozbay

We introduce here a simple finite-dimensional feedback control scheme for stabilizing solutions of infinite-dimensional dissipative evolution equations, such as reaction-diffusion systems, the Navier-Stokes equations and the…

Analysis of PDEs · Mathematics 2014-05-26 Abderrahim Azouani , Edriss S. Titi

This paper explores the decentralized control of linear deterministic systems in which different controllers operate based on distinct state information, and extends the findings to the output feedback scenario. Assuming the controllers…

Optimization and Control · Mathematics 2024-09-09 Hongdan Li , Yawen Sun , Huanshui Zhang

This paper considers a disturbance attenuation problem for a linear discrete time invariant system under random disturbances with imprecisely known probability distributions. The statistical uncertainty is measured in terms of relative…

Systems and Control · Computer Science 2015-03-19 Michael M. Tchaikovsky , Alexander P. Kurdyukov , Victor N. Timin

This paper addresses the formation maneuver control problem of leader-follower multi-agent systems with high-order integrator dynamics. A distributed output feedback formation maneuver controller is proposed to achieve desired maneuvers so…

Systems and Control · Electrical Eng. & Systems 2023-12-20 Xu Fang , Lihua Xie

This paper proposes a robust dual-quaternion based H-infinity task-space kinematic controller for robot manipulators. To address the manipulator liability to modeling errors, uncertainties, exogenous disturbances, and their influence upon…

Robotics · Computer Science 2021-06-22 Luis Felipe Cruz Figueredo , Bruno Vilhena Adorno , João Yoshiyuki Ishihara

Design of optimal distributed linear feedback controllers to achieve a desired aggregate behavior, while simultaneously satisfying state and input constraints, is a challenging but important problem in many applications. System level…

Optimization and Control · Mathematics 2022-11-07 Panagiotis D. Grontas , Michael W. Fisher , Florian Dörfler

This paper is concerned with the distributed control and stabilization problems for linear discrete-time large scale systems with imposed constraints. The main contributions of this paper are: Firstly, by using the maximum principle…

Optimization and Control · Mathematics 2018-01-03 Qingyuan Qi , Huanshui Zhang , Peijun Ju

Optimal control theory is a powerful tool for improving figures of merit in quantum information tasks. Finding the solution to any optimal control problem via numerical optimization depends crucially on the choice of the optimization…

In this paper, we give a causal solution to the problem of spline interpolation using H-infinity optimal approximation. Generally speaking, spline interpolation requires filtering the whole sampled data, the past and the future, to…

Information Theory · Computer Science 2013-08-14 Masaaki Nagahara , Yutaka Yamamoto

Predictive control is frequently used for control problems involving constraints. Being an optimization based technique utilizing a user specified so-called stage cost, performance properties, i.e., bounds on the infinite horizon…

Systems and Control · Electrical Eng. & Systems 2022-09-09 Lukas Beckenbach , Stefan Streif

This paper studies the boundary feedback stabilization of a class of diagonal infinite-dimensional boundary control systems. In the studied setting, the boundary control input is subject to a constant delay while the open loop system might…

Optimization and Control · Mathematics 2020-12-29 Hugo Lhachemi , Christophe Prieur

Analyzing and controlling system entropy is a powerful tool for regulating predictability of control systems. Applications benefiting from such approaches range from reinforcement learning and data security to human-robot collaboration. In…

Systems and Control · Electrical Eng. & Systems 2026-03-06 Menno van Zutphen , Giannis Delimpaltadakis , Duarte J. Antunes