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Predictor-based stabilization results are provided for nonlinear systems with input delays and a compact absorbing set. The control scheme consists of an inter-sample predictor, a global observer, an approximate predictor, and a nominal…

Optimization and Control · Mathematics 2013-06-17 Iasson Karafyllis , Miroslav Krstic , Tarek Ahmed-Ali , Francoise Lamnabhi-Lagarrigue

The mathematical theory of quantum feedback networks has recently been developed for general open quantum dynamical systems interacting with bosonic input fields. In this article we show, for the special case of linear dynamical systems…

Quantum Physics · Physics 2009-01-12 J. Gough , R. Gohm , M. Yanagisawa

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

We consider inverse problems estimating distributed parameters from indirect noisy observations through discretization of continuum models described by partial differential or integral equations. It is well understood that the errors…

Numerical Analysis · Mathematics 2023-10-09 Albero Bocchinfuso , Daniela Calvetti , Erkki Somersalo

A general input-output modelling technique for aperiodic-sampling linear systems has been developed. The procedure describes the dynamics of the system and includes the sequence of sampling periods among the variables to be handled. Some…

Discrete Mathematics · Computer Science 2016-08-14 Amparo Fúster-Sabater , J. M. Guillén

A single dynamical system with time-delayed feedback can emulate networks. This property of delay systems made them extremely useful tools for Machine Learning applications. Here we describe several possible setups, which allow emulating…

Dynamical Systems · Mathematics 2021-06-30 Florian Stelzer , Serhiy Yanchuk

This paper is devoted to the development of adaptive control schemes for uncertain discrete-time systems, which guarantee robust, global, exponential convergence to the desired equilibrium point of the system. The proposed control scheme…

Optimization and Control · Mathematics 2015-09-02 Iasson Karafyllis , Maria Kontorinaki , Markos Papageorgiou

Data-driven optimization of transmitters and receivers can reveal new modulation and detection schemes and enable physical-layer communication over unknown channels. Previous work has shown that practical implementations of this approach…

Signal Processing · Electrical Eng. & Systems 2019-11-05 Jinxiang Song , Bile Peng , Christian Häger , Henk Wymeersch , Anant Sahai

In this paper we propose a data-driven output-feedback controller synthesis method for discrete-time linear time-invariant systems in a specific autoregressive form. The synthesis goal is either to achieve dissipativity with respect to a…

Optimization and Control · Mathematics 2026-04-03 Pietro Kristović , Andrej Jokić , Mircea Lazar

We propose a novel feedback controller for a class of uncertain higher-order nonlinear systems, subject to delays in both state measurement and control input signals. Building on the prescribed performance control framework, a…

Optimization and Control · Mathematics 2025-09-11 Thomas Berger , Lampros N. Bikas , Jan Hachmeister , George A. Rovithakis

Using a new implicit discretization scheme, we study in this paper the existence and uniqueness of strong solutions for a class of Lur'e dynamical systems where the set-valued feedback depends on both time and state. This work is a…

Optimization and Control · Mathematics 2019-03-06 Ba Khiet Le

A novel control design approach for general nonlinear systems is presented in this paper. The approach is based on the identification of a polynomial model of the system to control and on the on-line inversion of this model. An efficient…

Systems and Control · Computer Science 2014-07-07 C. Novara , M. Milanese

The note focuses on the differential geometric approach to the study of nonlinear systems that are affine in control. We first develop normal forms for nonlinear system affine in control. Based on these normal forms, we then address the…

Dynamical Systems · Mathematics 2017-07-18 Xinmin Liu

Negative feedback is a powerful approach capable of improving several aspects of a system. In linear electronics, it has been critical for allowing invariance to device properties. Negative feedback is also known to enhance linearity in…

Instrumentation and Detectors · Physics 2016-11-22 Luciano da F. Costa , Filipi N. Silva , Cesar H. Comin

A learning approach for optimal feedback gains for nonlinear continuous time control systems is proposed and analysed. The goal is to establish a rigorous framework for computing approximating optimal feedback gains using neural networks.…

Optimization and Control · Mathematics 2020-08-27 Karl Kunisch , Daniel Walter

Time series data that are not measured at regular intervals are commonly discretized as a preprocessing step. For example, data about customer arrival times might be simplified by summing the number of arrivals within hourly intervals,…

Machine Learning · Statistics 2018-10-09 Peter Schulam , Suchi Saria

Prediction-based transformation is applied to control-affine systems with distributed input delays. Transformed system state is calculated as a prediction of the system's future response to the past input with future input set to zero.…

Optimization and Control · Mathematics 2016-01-05 Anton Ponomarev

In this paper, stability analysis of time delay systems is considered based on decomposition of the systems to subsystems. The decomposition process needs matrices of these systems to be simultaneously block triangularize. We show that a…

Optimization and Control · Mathematics 2016-11-29 Mohammad Mousa-Abadian , Sayed Hodjatollah Momeni-Masuleh , Mohammad Haeri

This paper presents a robust MPC scheme for linear systems subject to time-varying, uncertain constraints that arise from uncertain environments. The predicted input sequence is parameterized over future environment states to guarantee…

Systems and Control · Electrical Eng. & Systems 2024-04-16 Philipp Buschermöhle , Taouba Jouini , Torsten Lilge , Matthias A. Müller

This paper studies the linear quadratic regulation (LQR) problem of unknown discrete-time systems via dynamic output feedback learning control. In contrast to the state feedback, the optimality of the dynamic output feedback control for…

Systems and Control · Electrical Eng. & Systems 2025-05-29 Kedi Xie , Martin Guay , Shimin Wang , Fang Deng , Maobin Lu