Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Feedback control systems

Feedback control systems

Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...

Control Systems

Control Systems

Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...

Open and closed-loop control systems

Open and closed-loop control systems

Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal and...

Controller Configurations

Controller Configurations

Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller aligns...

Effects of feedback

Effects of feedback

Feedback in control systems plays a critical role in shaping various operational parameters, extending beyond simple error reduction to influence stability, bandwidth, gain, impedance, and sensitivity. Understanding these effects requires examining a basic feedback system characterized by defined input, output, error, and feedback signals.
Feedback significantly modifies the gain of a control system. The gain of a system without feedback is altered by a factor of one plus GH, where G represents...

Time-Domain Interpretation of PD Control

Time-Domain Interpretation of PD Control

Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Motor activation in cue-guided behavior: Neural evidence from human Pavlovian-to-instrumental transfer (PIT).

NeuroImage·2026

Same author

Revisiting our primate roots in infants grooming.

Scientific reports·2026

Same author

Tracing the Cognitive-Motor Connection: Prospective-Longitudinal Associations Between Early Parent-Toddler Literacy Activities and Subsequent Gross Motor Skills at School Entry.

Children (Basel, Switzerland)·2025

Same author

Coexistence of two adaptation processes in a visuomotor rotation task.

Journal of neurophysiology·2025

Same author

GEPPETO-OFC: An optimal feedback speech motor control model integrating biomechanical constraints and multisensory goal specification.

JASA express letters·2025

Same author

Theoretical and Practical Neuroscience Tools for Neurosurgery.

Advances and technical standards in neurosurgery·2025

Same journal

Can Neuroscience Inform Peacebuilding?

The European journal of neuroscience·2026

Same journal

Game-Based Foreign-Language Speech Rehearsal Improves Pitch Processing Beyond Speech Domain.

The European journal of neuroscience·2026

Same journal

Sleep Oscillations Across Cortical, Subcortical and Cerebellar Structures in Magnetoencephalography.

The European journal of neuroscience·2026

Same journal

Freezing of Gait Levodopa Response Pattern in Parkinson's Disease Provides Clues to Pathophysiology.

The European journal of neuroscience·2026

Same journal

Cognitive Flexibility and Bilingual Language Switching: An fMRI Meta-Analysis.

The European journal of neuroscience·2026

Same journal

Improved Motor Neuron Preservation and Axonal Recovery Following Experimental Sciatic Nerve Repair With Heterologous Fibrin Biopolymer.

The European journal of neuroscience·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 7, 2026

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

Computational motor control: feedback and accuracy.

Emmanuel Guigon¹, Pierre Baraduc, Michel Desmurget

¹INSERM U742, ANIM, Université Pierre et Marie Curie (UPMC - Paris 6), 9, quai Saint-Bernard, 75005 Paris, France. guigon@ccr.jussieu.fr

The European Journal of Neuroscience

|February 19, 2008

Summary

This summary is machine-generated.

Motor variability arises from the interplay of sensory and motor noise. This new model explains Fitts' law violations and movement accuracy, offering a unified framework for motor control research.

More Related Videos

A Method for Evaluating Timeliness and Accuracy of Volitional Motor Responses to Vibrotactile Stimuli

A Method for Evaluating Timeliness and Accuracy of Volitional Motor Responses to Vibrotactile Stimuli

Published on: August 2, 2016

Force and Position Control in Humans - The Role of Augmented Feedback

Force and Position Control in Humans - The Role of Augmented Feedback

Published on: June 19, 2016

Related Experiment Videos

Last Updated: Jul 7, 2026

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

A Method for Evaluating Timeliness and Accuracy of Volitional Motor Responses to Vibrotactile Stimuli

A Method for Evaluating Timeliness and Accuracy of Volitional Motor Responses to Vibrotactile Stimuli

Published on: August 2, 2016

Force and Position Control in Humans - The Role of Augmented Feedback

Force and Position Control in Humans - The Role of Augmented Feedback

Published on: June 19, 2016

Area of Science:

Motor control
Neuroscience
Biomechanics

Background:

The speed/accuracy trade-off in motor behavior is often explained by signal-dependent noise (SDN) in motor commands.
However, existing models fail to explain violations of Fitts' law, particularly during new skill acquisition.

Purpose of the Study:

To propose a principled framework for understanding motor variability.
To investigate the influence of sensory and motor execution noise on motor behavior.
To explain Fitts' law violations and movement accuracy within an optimal feedback control system.

Main Methods:

Developed a theoretical model of motor variability based on optimal feedback control.
Analyzed the interplay between signal-dependent sensory (proprioceptive) noise and signal-dependent motor noise.
Investigated the conditions under which Fitts' law is observed and violated.

Main Results:

Fitts' law emerges from signal-dependent motor noise (SDN(m)) with low sensory noise (e.g., visual feedback).
Terminal variability in non-visual movements is explained by signal-dependent proprioceptive noise.
Movement accuracy is modulated by opposing changes in signal-dependent sensory (SDN(s)) and motor noise (SDN(m)), potentially via co-contraction.

Conclusions:

The proposed optimal feedback control framework unifies explanations for motor variability, including Fitts' law and its violations.
The model accounts for kinematic, kinetic, muscular, and neural aspects of reaching movements.
This provides a comprehensive approach to understanding the complexities of motor control and adaptation.