Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

PI Controller: Design01:24

PI Controller: Design

433
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
433
Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

187
Proportional-Integral (PI) controllers are essential in many control systems to improve stability and performance. They are commonly used in everyday devices like thermostats to enhance system damping and reduce steady-state error. When the zero in the controller's transfer function is optimally placed, the system benefits significantly in terms of stability and accuracy.
Acting as a low-pass filter, the PI controller slows the system's response and extends settling times. This requires...
187
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

167
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...
167
Feedback control systems01:26

Feedback control systems

387
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...
387
PD Controller: Design01:26

PD Controller: Design

320
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
320
Open and closed-loop control systems01:17

Open and closed-loop control systems

932
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...
932

You might also read

Related Articles

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

Sort by
Same author

Study on the Modeling and Compensation Method of Pose Error Analysis for the Fracture Reduction Robot.

Micromachines·2022
Same author

Automatic Femoral Deformity Analysis Based on the Constrained Local Models and Hough Forest.

Journal of digital imaging·2022
Same author

Optimization of electronic prescription for parallel external fixator based on genetic algorithm.

International journal of computer assisted radiology and surgery·2019
Same author

The computer-aided parallel external fixator for complex lower limb deformity correction.

International journal of computer assisted radiology and surgery·2017
Same author

[A seroepidemiologic analysis of hepatitis B in Sichuan province].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2009
Same author

[Efficacy and safety of drospirenone-ethinylestradiol on contraception in healthy Chinese women: a multicenter randomized controlled trial].

Zhonghua fu chan ke za zhi·2009

Related Experiment Video

Updated: Aug 27, 2025

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
06:58

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

9.6K

Impedance Iterative Learning Backstepping Control for Output-Constrained Multisection Continuum Arms Based on PMA.

Yuexuan Xu1,2, Xin Guo1,2, Jian Li3,4

  • 1School of Artificial Intelligence and Data Science, Hebei University of Technology, Tianjin 300400, China.

Micromachines
|September 23, 2022
PubMed
Summary
This summary is machine-generated.

This study presents a novel control strategy for pneumatic muscle actuator (PMA) driven continuum arms, achieving precise trajectory tracking and stable force control. The method ensures accurate arm movement within defined constraints.

Keywords:
ANSYS/ADAMS/MATLABadaptive ILC with initial errorbarrier Lyapunov functionconstant curvature modelmultisection continuum arms

More Related Videos

Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs
03:55

Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs

Published on: October 27, 2023

2.2K
Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
10:32

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Published on: August 15, 2016

15.6K

Related Experiment Videos

Last Updated: Aug 27, 2025

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
06:58

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

9.6K
Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs
03:55

Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs

Published on: October 27, 2023

2.2K
Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
10:32

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Published on: August 15, 2016

15.6K

Area of Science:

  • Robotics
  • Control Systems Engineering

Background:

  • Pneumatic muscle actuators (PMAs) offer high flexibility and bionic properties for continuum arms.
  • Kinematic modeling and control of these arms present significant challenges.

Purpose of the Study:

  • To develop an effective kinematic model and control strategy for PMA-actuated multisection continuum arms.
  • To address challenges in precise trajectory tracking and force control.

Main Methods:

  • A geometric method under piecewise constant curvature assumption derived deformation parameters.
  • An improved D-H method established the kinematic model.
  • An impedance iterative learning backstepping control strategy was developed, incorporating iterative learning control (ILC) and a log-type barrier Lyapunov function.

Main Results:

  • Cosimulation demonstrated that the tracking error of the PMA converges to 0.004 m.
  • The tracking error remained within the time-varying constraint function.

Conclusions:

  • The proposed control strategy and kinematic modeling are superior and valid for PMA-actuated continuum arms.
  • The findings validate the effectiveness of the developed impedance iterative learning backstepping control.