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Related papers: Intermittent Control in Man and Machine

200 papers

Control and planning of multi-agent systems is an active and increasingly studied topic of research, with many practical applications such as rescue missions, security, surveillance, and transportation. This thesis addresses the planning…

Systems and Control · Electrical Eng. & Systems 2023-03-03 Christos Verginis

The human brain is a complex network that supports mental function. The nascent field of network neuroscience applies tools from mathematics to neuroimaging data in the hopes of shedding light on cognitive function. A critical question…

Neurons and Cognition · Quantitative Biology 2017-04-26 John D. Medaglia , Perry Zurn , Walter Sinnott-Armstrong , Danielle S. Bassett

Biological systems often choose actions without an explicit reward signal, a phenomenon known as intrinsic motivation. The computational principles underlying this behavior remain poorly understood. In this study, we investigate an…

Artificial Intelligence · Computer Science 2023-01-05 Stas Tiomkin , Ilya Nemenman , Daniel Polani , Naftali Tishby

Prediction and optimisation of a wheel loader's dynamic behaviour is a challenge due to tightly coupled, non-linear subsystems of different technical domains. Furthermore, a simulation regarding performance, efficiency, and operability…

Computational Engineering, Finance, and Science · Computer Science 2011-08-30 Reno Filla

The event-triggered control with intermittent output can reduce the communication burden between the controller and plant side over the network. It has been exploited for adaptive output feedback control of uncertain nonlinear systems in…

Systems and Control · Electrical Eng. & Systems 2026-03-26 Gewei Zuo , Lijun Zhu

Control theory arose from a need to control synthetic systems. From regulating steam engines to tuning radios to devices capable of autonomous movement, it provided a formal mathematical basis for understanding the role of feedback in the…

With the goal of increasing the speed and efficiency in robotic manipulation, a control approach is presented that aims to utilize intentional simultaneous impacts to its advantage. This approach exploits the concept of the time-invariant…

Robotics · Computer Science 2024-11-18 Jari van Steen , Nathan van de Wouw , Alessandro Saccon

We present the observation that the process of stochastic model predictive control can be formulated in the framework of iterated function systems. The latter has a rich ergodic theory that can be applied to study the system's long-run…

Optimization and Control · Mathematics 2022-10-14 Vyacheslav Kungurtsev , Jakub Marecek , Robert Shorten

We investigate how dynamical decoupling methods may be used to manipulate the time evolution of quantum many-body systems. These methods consist of sequences of external control operations designed to induce a desired dynamics. The systems…

Quantum Physics · Physics 2015-05-18 Julie Dinerman , Lea F. Santos

The control systems are an essential part of every engineering system in any industrial application. The basic purpose of controls is to manage the internal operations of the system and detect any unwanted or uncertain situation. Failure in…

Systems and Control · Electrical Eng. & Systems 2022-02-04 Raffay Yaqoob

No mixed research of hybrid and fractional-order systems into a cohesive and multifaceted whole can be found in the literature. This paper focuses on such a synergistic approach of the theories of both branches, which is believed to give…

Systems and Control · Computer Science 2014-07-25 S. Hassan HosseinNia , Ines Tejado , Blas M. Vinagre

This paper studies periodic event-triggered networked control for nonlinear systems, where the plants and controllers are connected by multiple independent communication channels. Several network-induced imperfections are considered…

Optimization and Control · Mathematics 2021-11-23 Hao Yu , Tongwen Chen

Learning-based control methods typically assume stationary system dynamics, an assumption often violated in real-world systems due to drift, wear, or changing operating conditions. We study reinforcement learning for control under…

Machine Learning · Computer Science 2026-04-03 Klemens Iten , Bruce Lee , Chenhao Li , Lenart Treven , Andreas Krause , Bhavya Sukhija

A novel model for dynamical traps in intermittent human control is proposed. It describes probabilistic, step-wise transitions between two modes of a subject's behavior - active and passive phases in controlling an object's dynamics - using…

Adaptation and Self-Organizing Systems · Physics 2025-03-04 Vasily Lubashevskiy , Ihor Lubashevsky , Namik Gusein-zade

Humans face the task of balancing dynamic systems near an unstable equilibrium repeatedly throughout their lives. Much research has been aimed at understanding the mechanisms of intermittent control in the context of human balance control.…

Neurons and Cognition · Quantitative Biology 2016-09-14 Arkady Zgonnikov , Ihor Lubashevsky

Control barrier functions have been demonstrated to be a useful method of ensuring constraint satisfaction for a wide class of controllers, however existing results are mostly restricted to continuous time systems of relative degree one.…

Robotics · Computer Science 2019-03-26 Wenceslao Shaw Cortez , Denny Oetomo , Chris Manzie , Peter Choong

In this paper, we present a model-based periodic event-triggered control mechanism for nonlinear continuous-time Networked Control Systems. A sampled-data prediction of the system behavior is used at the actuator to reduce the amount of…

Systems and Control · Electrical Eng. & Systems 2020-02-03 Michael Hertneck , Steffen Linsenmayer , Frank Allgöwer

Game dynamics structure (e.g., endogenous cycle motion) in human subjects game experiments can be predicted by game dynamics theory. However, whether the structure can be controlled by mechanism design to a desired goal is not known. Here,…

Theoretical Economics · Economics 2022-03-14 Wang Zhijian

Predicting how the brain can be driven to specific states by means of internal or external control requires a fundamental understanding of the relationship between neural connectivity and activity. Network control theory is a powerful tool…

Neurons and Cognition · Quantitative Biology 2019-08-12 Teresa M. Karrer , Jason Z. Kim , Jennifer Stiso , Ari E. Kahn , Fabio Pasqualetti , Ute Habel , Danielle S. Bassett

Biological systems perform an astonishing array of dynamical processes -- including development and repair, regulation, behavior and motor control, sensing and signaling, and adaptation, among others. Powered by the transduction of stored…

Soft Condensed Matter · Physics 2025-09-04 James Clarke , Jake McGrath , Colin Johnson , José Alvarado