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

467
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...
467
Phase-lead and Phase-lag Controllers01:22

Phase-lead and Phase-lag Controllers

612
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...
612
Second Order systems II01:18

Second Order systems II

465
In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
465
PI Controller: Design01:24

PI Controller: Design

1.4K
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...
1.4K
PID Controller01:19

PID Controller

901
Proportional-Integral-Derivative (PID) controllers are widely used in various control systems to enhance stability and performance. In a thermostat, it adjusts heating or cooling based on the temperature difference between the actual and desired levels. They are often used in automotive speed systems, effectively managing sudden speed changes while maintaining a constant speed under varying conditions. On the other hand, PI controllers, commonly employed in voltage regulation, enhance stability...
901
PD Controller: Design01:26

PD Controller: Design

694
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,...
694

You might also read

Related Articles

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

Sort by
Same author

Time-varying sliding mode control based finite-time prescribed performance function for robotic manipulators.

ISA transactions·2025
Same author

Enhancing Multi-Label Chest X-Ray Classification Using an Improved Ranking Loss.

Bioengineering (Basel, Switzerland)·2025
Same author

A Comprehensive Study of Recent Path-Planning Techniques in Dynamic Environments for Autonomous Robots.

Sensors (Basel, Switzerland)·2025
Same author

Medical ultrasound image speckle reduction and resolution enhancement using texture compensated multi-resolution convolution neural network.

Frontiers in physiology·2022
Same author

Resilience-Building for Mental Health among Early Childhood Educators: A Systematic Review and Pilot-Study towards an EEG-VR Resilience Building Intervention.

International journal of environmental research and public health·2022
Same author

Performance Evaluation of EEG Based Mental Stress Assessment Approaches for Wearable Devices.

Frontiers in neurorobotics·2022

Related Experiment Video

Updated: Mar 21, 2026

Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

3.0K

Closed-loop step response for tuning PID-fractional-order-filter controllers.

Karima Amoura1, Rachid Mansouri1, Maâmar Bettayeb2

  • 1L2CSP Laboratory, Mouloud Mammeri University, Tizi Ouzou, Algeria.

ISA Transactions
|May 11, 2016
PubMed
Summary
This summary is machine-generated.

A new empirical method tunes fractional-order PID controllers (FOF-PID) using a simple step response experiment. This approach offers advantages over model-based methods, directly yielding controller parameters without plant identification.

Keywords:
Fractional order controllerInternal model controlPID controllerRobust control

More Related Videos

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

14.3K
Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

9.2K

Related Experiment Videos

Last Updated: Mar 21, 2026

Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

3.0K
An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

14.3K
Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

9.2K

Area of Science:

  • Control Engineering
  • Process Control
  • Automation Systems

Background:

  • Traditional tuning of fractional controllers relies on complex analytical methods.
  • The PID-Fractional-Order-Filter (FOF-PID) controller offers advanced control capabilities.
  • Model-based tuning rules, like Internal Model Control (IMC), require a plant model.

Purpose of the Study:

  • To propose an empirical, model-free tuning method for the FOF-PID controller.
  • To adapt the setpoint overshoot method for tuning the FOF-PID controller.
  • To demonstrate the effectiveness and advantages of the proposed tuning approach.

Main Methods:

  • Adaptation of the setpoint overshoot method for FOF-PID controller tuning.
  • Derivation of correlations from simulations of first-order plus time-delay processes.
  • Comparison with Internal Model Control (IMC) tuning and other relevant techniques.

Main Results:

  • The proposed empirical method yields FOF-PID controller parameters comparable to IMC.
  • The method requires only a single closed-loop step response experiment with a P-controller.
  • Performance is validated through various case studies, showing comparable or superior results to IMC.

Conclusions:

  • The adapted setpoint overshoot method provides an effective, model-free tuning solution for FOF-PID controllers.
  • This empirical approach simplifies controller tuning by directly using experimental data.
  • The method offers practical advantages, eliminating the need for explicit plant model identification.