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

PID Controller01:19

PID Controller

410
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...
410
Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

277
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...
277
PI Controller: Design01:24

PI Controller: Design

845
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...
845
PD Controller: Design01:26

PD Controller: Design

464
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,...
464
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

243
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...
243
Second Order systems I01:20

Second Order systems I

378
A servo system exemplifies a second-order system, featuring a proportional controller and load elements that ensure the output position aligns with the input position. The relationship between these components is described by a second-order differential equation. Applying the Laplace transform under zero initial conditions yields the transfer function, showing how inputs are converted to outputs in the system.
By reinterpreting the system, one can derive the closed-loop transfer function, which...
378

You might also read

Related Articles

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

Sort by
Same author

The mouse-lethal H5N1 influenza virus carrying the PB2-384L/443R/460M characteristics acquired in avian hosts can effectively utilize human ANP32A/B proteins.

Emerging microbes & infections·2026
Same author

Chuangling Liquid Mitigates Plasma Cell Mastitis via STAT3 Pathway Inhibition: Pharmacological and Experimental Insights.

Combinatorial chemistry & high throughput screening·2026
Same author

A nanobody-based proteolysis-targeting chimera offers broad-spectrum protection against diverse influenza virus infections.

Signal transduction and targeted therapy·2026
Same author

Syrian hamster is a valuable animal model for evaluating the transmissibility of emerging influenza viruses.

Emerging microbes & infections·2026
Same author

Replication and Transmission of Influenza A Virus in Farmed Mink.

Viruses·2026
Same author

A Portable One-Tube Assay Integrating RT-RPA and CRISPR/Cas12a for Rapid Visual Detection of Eurasian Avian-like H1N1 Swine Influenza Virus in the Field.

Viruses·2026

Related Experiment Video

Updated: Nov 23, 2025

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

2.8K

Mathematical analysis of a simplified general type-2 fuzzy PID controller.

Jianzhong Shi1, Ying Song1

  • 1School of Energy and Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China.

Mathematical Biosciences and Engineering : MBE
|December 31, 2020
PubMed
Summary

A simplified general type-2 fuzzy PID (SGT2-FPID) controller reduces computation complexity. This robust controller demonstrates superior performance in uncertain plant conditions compared to traditional fuzzy PID controllers.

Keywords:
fuzzy controller structure analysistype reductiontype-2 fuzzy controllertype-2 fuzzy logic systemstype-2 fuzzy sets

More Related Videos

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

2.0K
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

14.0K

Related Experiment Videos

Last Updated: Nov 23, 2025

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

2.8K
Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

2.0K
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

14.0K

Area of Science:

  • Control Engineering
  • Fuzzy Logic Systems
  • Computational Intelligence

Background:

  • General type-2 fuzzy PID controllers are computationally intensive and mathematically complex.
  • Type reduction is a critical but time-consuming step in their implementation.
  • Existing methods often lack robustness in uncertain environments.

Purpose of the Study:

  • To introduce a Simplified General Type-2 Fuzzy PID (SGT2-FPID) controller.
  • To reduce the computational complexity of type reduction for type-2 fuzzy PID controllers.
  • To analyze the mathematical expressions of SGT2-FPID, type-1 fuzzy PID, and interval type-2 fuzzy PID controllers.

Main Methods:

  • Utilizing triangular membership functions for both primary and secondary membership functions.
  • Employing the primary membership degree of the apex of the secondary membership degree for output calculation.
  • Deriving and comparing mathematical expressions for SGT2-FPID, type-1 fuzzy PID, and interval type-2 fuzzy PID controllers.
  • Simulating the SGT2-FPID controller on four different plant models.

Main Results:

  • The SGT2-FPID controller significantly reduces computational complexity in type reduction.
  • Mathematical expressions for SGT2-FPID, type-1 fuzzy PID, and interval type-2 fuzzy PID are derived and discussed.
  • The SGT2-FPID controller exhibits enhanced robustness and control performance.
  • Superior performance is observed even with model uncertainties, measurement noise, and external disturbances.

Conclusions:

  • The SGT2-FPID controller offers an effective and computationally efficient alternative to traditional type-2 fuzzy PID controllers.
  • Its simplified structure and robust performance make it suitable for applications with inherent uncertainties.
  • The study validates the practical applicability and advantages of the SGT2-FPID controller in complex control scenarios.