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

PD Controller: Design01:26

PD Controller: Design

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

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...
PID Controller01:19

PID Controller

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...
PI Controller: Design01:24

PI Controller: Design

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...
Controller Configurations01:22

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...
Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

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 careful...

You might also read

Related Articles

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

Sort by
Same author

Fault Diagnosis of Rotary Machines Using Deep Convolutional Neural Network with Wide Three Axis Vibration Signal Input.

Sensors (Basel, Switzerland)·2020
Same author

Modeling and control of a pneumatically actuated inverted pendulum.

ISA transactions·2009
See all related articles

Related Experiment Video

Updated: May 7, 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

PID controller auto-tuning based on process step response and damping optimum criterion.

Danijel Pavković1, Siniša Polak2, Davor Zorc1

  • 1Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, I. Lučića 5, HR-10000 Zagreb, Croatia.

ISA Transactions
|September 17, 2013
PubMed
Summary

A new PID controller tuning method uses an n-th order lag (PTn) process model and damping optimum criterion for auto-tuning. This approach simplifies adjustments for response speed and damping in higher-order systems.

Keywords:
Auto-tuning controlDamping optimum criterionIdentificationPID controllerPTn process model

Related Experiment Videos

Last Updated: May 7, 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

Area of Science:

  • Control Engineering
  • Process Automation
  • System Identification

Background:

  • Proportional-Integral-Derivative (PID) controllers are widely used in industrial automation.
  • Tuning PID controllers for higher-order aperiodic processes can be complex and time-consuming.
  • Existing auto-tuning methods may not be optimal for all process types.

Purpose of the Study:

  • To present a novel PID controller tuning method for higher-order aperiodic processes.
  • To enable step response-based auto-tuning applications.
  • To provide straightforward algebraic rules for adjusting closed-loop response speed and damping.

Main Methods:

  • Identification of an n-th order lag (PTn) process model from the process step response.
  • Novel evaluation of PTn model parameters using equivalent dead-time and lag time constant.
  • Application of the damping optimum criterion for PID controller tuning.

Main Results:

  • A straightforward algebraic method for PID controller parameter adjustment.
  • Effective tuning for both response speed and damping of higher-order systems.
  • Successful verification of the method through extensive computer simulations.

Conclusions:

  • The proposed PTn model identification and damping optimum-based PID tuning is effective for higher-order aperiodic processes.
  • The method offers a simplified approach to PID auto-tuning.
  • This technique enhances the performance and applicability of PID controllers in industrial settings.