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The methodology of funnel control was introduced in the early 2000s, and it has developed since then in many respects achieving a level of mathematical maturity balanced by practical applications. Its fundamental tenet is the attainment of…

Optimization and Control · Mathematics 2025-07-03 Thomas Berger , Achim Ilchmann , Eugene P. Ryan

In this paper, fractional order Coullet system is studied. An active control technique is applied to control this chaotic system. This type of controller is also applied to synchronize chaotic fractional-order systems in master-slave…

Chaotic Dynamics · Physics 2012-06-13 M. Shahiri T. , A. Ranjbar N. , R. Ghaderi , S. H. Hosseinnia , S. Momani

This paper develops the theoretical foundations for the ability of a control field to cooperate with noise in the manipulation of quantum dynamics. The noise enters as run-to-run variations in the control amplitudes, phases and frequencies…

Quantum Physics · Physics 2009-11-13 Feng Shuang , Herschel Rabitz , Mark Dykman

In many control system applications, state constraint satisfaction needs to be guaranteed within a prescribed time. While this issue has been partially addressed for systems with known dynamics, it remains largely unaddressed for systems…

Systems and Control · Electrical Eng. & Systems 2024-06-14 Tzu-Yuan Huang , Sihua Zhang , Xiaobing Dai , Alexandre Capone , Velimir Todorovski , Stefan Sosnowski , Sandra Hirche

We present a stochastic model predictive control framework for nonlinear systems subject to unbounded process noise with closed-loop guarantees. First, we provide a conceptual shrinking-horizon framework that utilizes general probabilistic…

Systems and Control · Electrical Eng. & Systems 2025-06-06 Johannes Köhler , Melanie N. Zeilinger

It is shown that a relevant control of Hamiltonian chaos is possible through suitable small perturbations whose form can be explicitly computed. In particular, it is possible to control (reduce) the chaotic diffusion in the phase space of a…

This paper focuses on the controller synthesis for unknown, nonlinear systems while ensuring safety constraints. Our approach consists of two steps, a learning step that uses Gaussian processes and a controller synthesis step that is based…

Systems and Control · Electrical Eng. & Systems 2020-10-13 Pushpak Jagtap , George J. Pappas , Majid Zamani

Partial trace is a very important mathematical operation in quantum mechanics. It is not only helpful in studying the subsystems of a composite quantum system but also used in computing a vast majority of quantum entanglement measures.…

Quantum Physics · Physics 2019-06-28 Pranay Barkataki , M. S. Ramkarthik

This paper deals with feedback control of fractional-order Chua's system. The fractional-order Chua's system with total order less than three which exhibit chaos as well as other nonlinear behavior and theory for control of chaotic systems…

Chaotic Dynamics · Physics 2007-05-23 I. Petras

The aim of this paper is to propose a new data-driven control scheme for multi-input-multi-output linear time-invariant systems whose system model are completely unknown. Using a non-minimal input-output realization, the proposed method can…

Systems and Control · Electrical Eng. & Systems 2022-01-11 Nam H. Jo , Hyungbo Shim

In this paper, we present a novel data-driven approach to quantify safety for non-linear, discrete-time stochastic systems with unknown noise distribution. We define safety as the probability that the system remains in a given region of the…

Systems and Control · Electrical Eng. & Systems 2024-10-10 Frederik Baymler Mathiesen , Licio Romao , Simeon C. Calvert , Luca Laurenti , Alessandro Abate

Control systems operating in the real world face countless sources of unpredictable uncertainties. These random disturbances can render deterministic guarantees inapplicable and cause catastrophic safety failures. To overcome this, this…

Systems and Control · Electrical Eng. & Systems 2026-02-10 Pol Mestres , Blake Werner , Ryan K. Cosner , Aaron D. Ames

The study of chaos has long relied on computationally intensive methods to quantify unpredictability and design control strategies. Recent advances in machine learning, from convolutional neural networks to transformer architectures,…

Chaotic Dynamics · Physics 2026-01-30 David Valle , Alexandre Wagemakers , Miguel A. F. Sanjuán

This paper presents a technique to drive the state of a constrained nonlinear system to a specified target state in finite time, when the system suffers a partial loss in control authority. Our technique builds on a recent method to control…

Optimization and Control · Mathematics 2026-04-10 Ram Padmanabhan , Melkior Ornik

This paper develops a new control design for guaranteeing a vehicle's safety during lane change maneuvers in a complex traffic environment. The proposed method uses a finite state machine (FSM), where a quadratic program based optimization…

Systems and Control · Electrical Eng. & Systems 2021-03-24 Suiyi He , Jun Zeng , Bike Zhang , Koushil Sreenath

In this paper, we propose a novel approach to synthesize linear feedback controllers for navigating in polygonal environments using noisy measurements and a convex cell decomposition. Our method is based on formulating chance constraints…

Optimization and Control · Mathematics 2020-12-22 Chenfei Wang , Mahroo Bahreinian , Roberto Tron

Stabilizing unstable periodic orbits in a chaotic invariant set not only reveals information about its structure but also leads to various interesting applications. For the successful application of a chaos control scheme, convergence speed…

Adaptation and Self-Organizing Systems · Physics 2016-10-10 Christian Bick , Marc Timme , Christoph Kolodziejski

We consider the problem of navigating a nonlinear dynamical system from some initial set to some target set while avoiding collision with an unsafe set. We extend the concept of density function to control density function (CDF) for solving…

Systems and Control · Electrical Eng. & Systems 2024-03-22 Joseph Moyalan , Sriram S. K. S Narayanan , Andrew Zheng , Umesh Vaidya

A chaos control algorithm is developed to actively stabilize unstable periodic orbits of higher-dimensional systems. The method assumes knowledge of the model equations and a small number of experimentally accessible parameters. General…

chao-dyn · Physics 2019-08-17 A. Pentek , J. B. Kadtke , Z. Toroczkai

This paper studies quantized control for discrete-time piecewise affine systems. For given stabilizing feedback controllers, we propose an encoding strategy for local stability. If the quantized state is near the boundaries of quantization…

Systems and Control · Computer Science 2015-09-07 Masashi Wakaiki , Yutaka Yamamoto
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