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

Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

211
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...
211
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

189
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...
189
PI Controller: Design01:24

PI Controller: Design

559
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...
559
Phase-lead and Phase-lag Controllers01:22

Phase-lead and Phase-lag Controllers

237
Understanding the working function of different types of controllers can be illustrated with practical analogies, such as adjusting a stereo's volume equalizer. Cranking up the bass involves a phase-lead controller, which functions as a high-pass filter, while increasing the treble uses a phase-lag controller, which acts as a low-pass filter. PD controllers, similar to high-pass filters, enhance the system's response to high-frequency components. PI controllers, akin to low-pass...
237
Time and frequency -Domain Interpretation of Phase-lead Control01:24

Time and frequency -Domain Interpretation of Phase-lead Control

144
Phase-lead controllers are commonly used in various control systems to enhance response speed and stability. Adjusting the brightness on a television screen offers a practical example of phase-lead control. When contrast is enhanced, a phase-lead controller is employed. Mathematically, phase-lead control is identified when the first parameter is smaller than the second.
The design of phase-lead control involves the strategic placement of poles and zeros to balance steady-state error and system...
144
PD Controller: Design01:26

PD Controller: Design

370
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,...
370

You might also read

Related Articles

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

Sort by
Same author

Hotspot Evolution and Future Prospects of Large Language Models in Medical Education: A Bibliometric Analysis.

Advances in medical education and practice·2026
Same author

Divergent pathogenic mechanisms of influenza A and influenza B viruses.

Archives of microbiology·2026
Same author

AARS2-mediated lactylation of ULK1 promotes autophagy-dependent progression of clear cell renal cell carcinoma.

Autophagy·2026
Same author

Development and external validation of a multivariable nomogram for predicting severe immune checkpoint inhibitor-associated myocarditis in advanced lung cancer.

Translational lung cancer research·2026
Same author

Performance comparison of large language models for medication counseling in people living with HIV.

Frontiers in public health·2026
Same author

Clinical Characteristics and Survival Outcomes in a Cohort of Pediatric Rhabdomyosarcoma Patients: The Impact of Risk-Adapted Therapy.

Cancers·2026

Related Experiment Video

Updated: Sep 28, 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

An Adaptive Time-Varying Impedance Controller for Manipulators.

Xu Liang1,2, Tingting Su1, Zhonghai Zhang3

  • 1Department of Mechanical and Electrical Engineering, North China University of Technology, Beijng, China.

Frontiers in Neurorobotics
|April 4, 2022
PubMed
Summary

This study introduces a novel adaptive impedance controller for robotic manipulators with uncertain parameters. The controller ensures stability without needing acceleration feedback or external load measurements, improving robotic control robustness.

Keywords:
MRACadaptivehuman–robot interactionintelligent controltime-varying

More Related Videos

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.7K
Method to Measure Tone of Axial and Proximal Muscle
10:41

Method to Measure Tone of Axial and Proximal Muscle

Published on: December 14, 2011

17.7K

Related Experiment Videos

Last Updated: Sep 28, 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
Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.7K
Method to Measure Tone of Axial and Proximal Muscle
10:41

Method to Measure Tone of Axial and Proximal Muscle

Published on: December 14, 2011

17.7K

Area of Science:

  • Robotics
  • Control Systems Engineering

Background:

  • General manipulators often have uncertain structural parameters, posing challenges for precise control.
  • Existing impedance control methods may require acceleration feedback or external load measurements, limiting their applicability.

Purpose of the Study:

  • To propose a time-varying impedance controller robust to uncertain structural parameters in general manipulators.
  • To develop a controller that does not require acceleration-based feedback or external load measurements.

Main Methods:

  • Model Reference Adaptive Control (MRAC) is employed to design the time-varying impedance controller.
  • Global uniform asymptotic stability analysis of the closed-loop system is performed.
  • A control parameter selection approach is presented.

Main Results:

  • The proposed controller tolerates considerable structure parameter errors.
  • The stability of the time-varying closed-loop system is proven.
  • The adaptive controller, with the proposed parameter selection, is shown to be equivalent to existing robust control results.

Conclusions:

  • The developed time-varying impedance controller effectively addresses parameter uncertainties in general manipulators.
  • The controller's feasibility and robustness are validated through numerical simulations.