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Recently developed control methods with strong disturbance rejection capabilities provide a useful option for control design. The key lies in a general concept of disturbance and effective ways to estimate and compensate the disturbance.…

Optimization and Control · Mathematics 2018-01-19 Wuhua Hu , Eduardo F. Camacho , Lihua Xie

Observing and controlling complex networks are of paramount interest for understanding complex physical, biological and technological systems. Recent studies have made important advances in identifying sensor or driver nodes, through which…

Effective and causal observable functions for low-order lifting linearization of nonlinear controlled systems are learned from data by using neural networks. While Koopman operator theory allows us to represent a nonlinear system as a…

Robotics · Computer Science 2021-08-04 Nicholas Stearns Selby , H. Harry Asada

We propose a new controllability property for linear time varying control systems in finite dimension: the nonuniform complete controllability, which is halfway between the classical Kalman's properties of complete controllability and…

Optimization and Control · Mathematics 2024-10-08 Ignacio Huerta , Pablo Monzón , Gonzalo Robledo

Differentiable physics is a powerful approach to learning and control problems that involve physical objects and environments. While notable progress has been made, the capabilities of differentiable physics solvers remain limited. We…

Machine Learning · Computer Science 2020-07-07 Yi-Ling Qiao , Junbang Liang , Vladlen Koltun , Ming C. Lin

Regulators and academics are increasingly interested in the causal effect that algorithmic actions of a digital platform have on consumption. We introduce a general causal inference problem we call the steerability of consumption that…

Machine Learning · Computer Science 2023-02-13 Gary Cheng , Moritz Hardt , Celestine Mendler-Dünner

By optimizing the predicted performance over a receding horizon, model predictive control (MPC) provides the ability to enforce state and control constraints. The present paper considers an extension of MPC for nonlinear systems that can be…

Systems and Control · Electrical Eng. & Systems 2023-09-29 Mohammadreza Kamaldar , Dennis S. Bernstein

For linear control systems, the usual state feedback stabilizability has two components: one is a continuous observation mode (i.e., to observe solutions continuously in time), and the other is a class of feedback laws (which is usually the…

Optimization and Control · Mathematics 2022-08-29 Hanbing Liu , Gengsheng Wang , Huaiqiang Yu

We consider a terminal control problem for processes governed by a nonlinear system of fractional ODEs. In order to show existence of the control, we first consider the linear counterpart of the system and reprove a number of classical…

Optimization and Control · Mathematics 2022-12-27 Maja Jolić , Sanja Konjik , Darko Mitrović

We introduce a data-based approach to estimating key quantities which arise in the study of nonlinear control systems and random nonlinear dynamical systems. Our approach hinges on the observation that much of the existing linear theory may…

Optimization and Control · Mathematics 2016-04-04 Jake Bouvrie , Boumediene Hamzi

Relative observability has been introduced and studied in the framework of partially observed discrete-event systems as a condition stronger than observability, but weaker than normality. However, unlike observability, relative…

Optimization and Control · Mathematics 2014-04-09 Jan Komenda , Tomáš Masopust , Jan H. van Schuppen

Controllability and observability energy functions play a fundamental role in model order reduction and are inherently connected to optimal control problems. For linear dynamical systems the energy functions are known to be quadratic…

Dynamical Systems · Mathematics 2025-02-11 Linus Balicki , Serkan Gugercin

This paper presents a new approach to Model Predictive Control for environments where essential, discrete variables are partially observed. Under this assumption, the belief state is a probability distribution over a finite number of…

Robotics · Computer Science 2023-02-02 Camille Phiquepal , Marc Toussaint

Tracking of reference signals is addressed in the context of a class of nonlinear controlled systems modelled by $r$-th order functional differential equations, encompassing inter alia systems with unknown "control direction" and dead-zone…

Optimization and Control · Mathematics 2021-01-18 Thomas Berger , Achim Ilchmann , Eugene P Ryan

Optimal nonlinear damping control was recently introduced for the second-order SISO systems, showing some advantages over a classical PD feedback controller. This paper summarizes the main theoretical developments and properties of the…

Systems and Control · Electrical Eng. & Systems 2022-08-09 Michael Ruderman

We are motivated by the problem of control for a non-homogeneous elastic string with memory. We reduce the problem of controllability to a non-standard moment problem. The solution of the latter problem is based on an auxiliary Riesz basis…

Optimization and Control · Mathematics 2011-10-28 Sergei A. Avdonin , Boris P. Belinskiy

Inverse optimal control can be used to characterize behavior in sequential decision-making tasks. Most existing work, however, is limited to fully observable or linear systems, or requires the action signals to be known. Here, we introduce…

Machine Learning · Computer Science 2023-10-31 Dominik Straub , Matthias Schultheis , Heinz Koeppl , Constantin A. Rothkopf

Differential stability of convex discrete optimal control problems in Banach spaces is studied in this paper. By using some recent results of An and Yen [Appl. Anal. 94, 108--128 (2015)] on differential stability of parametric convex…

Optimization and Control · Mathematics 2017-07-12 Duong Thi Viet An , Nguyen Thi Toan

In this paper, nonlinear model reduction for power systems is performed by the balancing of empirical controllability and observability covariances that are calculated around the operating region. Unlike existing model reduction methods,…

Systems and Control · Computer Science 2016-08-30 Junjian Qi , Jianhui Wang , Hui Liu , Aleksandar D. Dimitrovski

Underactuated robots are characterized by a larger number of degrees of freedom than actuators and if they are designed with a specific mass distribution, they can be controlled by means of differential flatness theory. This structural…

Robotics · Computer Science 2026-04-21 Stefano Lovato , Michele Tonan , Matteo Bottin , Matteo Massaro , Alberto Doria , Giulio Rosati