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This work explores the trade-off between the number of samples required to accurately build models of dynamical systems and the degradation of performance in various control objectives due to a coarse approximation. In particular, we show…

Optimization and Control · Mathematics 2017-12-01 Stephen Tu , Ross Boczar , Andrew Packard , Benjamin Recht

Real-world control applications in complex and uncertain environments require adaptability to handle model uncertainties and robustness against disturbances. This paper presents an online, output-feedback, critic-only, model-based…

Systems and Control · Electrical Eng. & Systems 2023-04-25 Tochukwu Elijah Ogri , Zachary I. Bell , Rushikesh Kamalapurkar

This paper investigates adaptive model predictive control (MPC) for a class of constrained linear systems with unknown model parameters. This is also posed as the dual control problem consisting of system identification and regulation. We…

Optimization and Control · Mathematics 2020-11-24 Kunwu Zhang , Yang Shi

Stability and control of a non-linear system represent an important system configuration that frequently arises in practical engineering. Stability covers a vast range of systems that do not obey the superposition principle and applies to…

Systems and Control · Electrical Eng. & Systems 2022-02-04 Asifa Yousaf

A re-entrant manufacturing system producing a large number of items and involving many steps can be approximately modeled by a hyperbolic partial differential equation (PDE) according to mass conservation law with respect to a continuous…

Optimization and Control · Mathematics 2016-11-15 Xiaodong Xu , Stevan Dubljevic

This paper addresses the design of robust dynamic output feedback control for highly uncertain systems in which the unknown disturbance might be excited by the derivative of the control input. This context appears in many industrial…

Systems and Control · Computer Science 2016-10-20 Mazen Alamir , Jean Dobrowolski , Amgad tarek Mohammed

The robust disturbance rejection controller has been the subject of intensive research due to its undeniable importance for automation. Modern control theory tends to use model-based approaches versus model-free approaches, especially when…

Systems and Control · Electrical Eng. & Systems 2022-01-03 Atta Oveisi

This paper studies the identification of nonlinearly parameterized control systems in given experiments. Several identifiability criteria are established and an implementable algorithm is proposed for practicality with the convergence rate…

Optimization and Control · Mathematics 2019-08-21 Chanying Li

A new systematic approach to the construction of approximate solutions to a class of nonlinear singularly perturbed feedback control systems using the boundary layer functions especially with regard to the possible occurrence of the…

Optimization and Control · Mathematics 2017-09-07 Robert Vrabel

This paper generalizes recent results by the authors on noninvasive model-reference adaptive control designs for control-based continuation of periodic orbits in periodically excited linear systems with matched uncertainties to a larger…

Optimization and Control · Mathematics 2023-01-02 Yang Li , Harry Dankowicz

In this paper, we consider the output synchronization problem for a network of heterogeneous diffusively-coupled nonlinear agents. Specifically, we show how the (non-identical) agents can be controlled in such a way that their outputs…

Optimization and Control · Mathematics 2013-03-13 A. Isidori , L. Marconi , G. Casadei

The paper deals with the control and regulation by integral controllers forthe nonlinear systems governed by scalar quasi-linear hyperbolic partial differentialequations. Both the control input and the measured output are located on the…

Analysis of PDEs · Mathematics 2019-04-30 Vincent Andrieu , Ngoc-Tu Trinh , Cheng-Zhong Xu

This paper presents tailor-made neural model structures and two custom fitting criteria for learning dynamical systems. The proposed framework is based on a representation of the system behavior in terms of continuous-time state-space…

Systems and Control · Electrical Eng. & Systems 2021-09-02 Marco Forgione , Dario Piga

We propose an extension of the input-output feedback linearization for a class of multivariate systems that are not input-output linearizable in a classical manner. The key observation is that the usual input-output linearization problem…

Systems and Control · Electrical Eng. & Systems 2025-03-13 Sang-ik An , Dongheui Lee , Gyunghoon Park

The present paper deals with the data-driven design of regularizers in the form of artificial neural networks, for solving certain inverse problems formulated as optimal control problems. These regularizers aim at improving accuracy,…

Optimization and Control · Mathematics 2023-03-06 Sebastien Court

In this paper, a multi-agent coordination problem with steady-state regulation constraints is investigated for a class of nonlinear systems. Unlike existing leader-following coordination formulations, the reference signal is not given by a…

Systems and Control · Computer Science 2017-08-15 Yutao Tang , Peng Yi

This work studies the design of safe control policies for large-scale non-linear systems operating in uncertain environments. In such a case, the robust control framework is a principled approach to safety that aims to maximize the…

Systems and Control · Computer Science 2019-03-04 Edouard Leurent , Yann Blanco , Denis Efimov , Odalric-Ambrym Maillard

This paper deals with the output regulation problem of a linear time-invariant system in the presence of sporadically available measurement streams. A regulator with a continuous intersample injection term is proposed, where the intersample…

Systems and Control · Electrical Eng. & Systems 2022-02-16 Himadri Basu , Francesco Ferrante , Se Young Yoon

A novel adaptive control approach is proposed to solve the globally asymptotic state stabilization problem for uncertain pure-feedback nonlinear systems which can be transformed into the pseudo-affine form. The pseudo-affine pure-feedback…

Systems and Control · Computer Science 2016-09-29 Mingzhe Hou , Zongquan Deng , Guangren Duan

We show how optimal nonlinear regulation can be achieved in a model predictive control fashion.

Optimization and Control · Mathematics 2013-10-29 Cesar O. Aguilar , Arthur J. Krener
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