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

764
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...
764
PID Controller01:19

PID Controller

361
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...
361
Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

264
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...
264
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

231
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...
231
PD Controller: Design01:26

PD Controller: Design

444
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,...
444
Feedback control systems01:26

Feedback control systems

548
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...
548

You might also read

Related Articles

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

Sort by
Same author

Gene regulatory networks orchestrating oocyte fate bifurcation in primordial follicles revealed by single-cell transcriptomics.

Communications biology·2026
Same author

Protective and risk factors for caregiver mental health: a mediation analysis in a rural Chinese cohort of mothers and grandmothers caring for young children.

BMC psychology·2026
Same author

Using Well-Defined DNA Nanostructures To Study the Influence of DNA Clustering and Presentation on SNA Cellular Uptake.

Nano letters·2026
Same author

Iron-Photocatalyzed C(sp<sup>3</sup>)-H Phosphonylation of Alkanes.

Angewandte Chemie (International ed. in English)·2026
Same author

Real-time minimalist imaging via spatial aberration uniformization and re-parameterized restoration.

Optics express·2026
Same author

EEG-based stroke severity classification using higher-order topological features and graph convolutional networks.

Frontiers in neuroscience·2026
Same journal

Stackelberg differential game-based fuzzy adaptive hierarchical optimal control for a nonlinear system with unknown dynamics.

ISA transactions·2026
Same journal

Composite fault-tolerant predictive control strategy for PMSM demagnetization faults.

ISA transactions·2026
Same journal

Bias-compensated Q-learning for optimal tracking control under denial-of-service attacks.

ISA transactions·2026
Same journal

Motion prediction for leader manipulator of teleoperation system with large time delay based on inverse optimal control.

ISA transactions·2026
Same journal

Neural network parameter identification-based prescribed-time adaptive control for morphing glide aircraft.

ISA transactions·2026
Same journal

Nonlinear system-guided continuous-time generalization for cross-aircraft engine state monitoring.

ISA transactions·2026
See all related articles

Related Experiment Video

Updated: Nov 12, 2025

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

8.8K

Non-singleton interval type-2 fuzzy PID control for high precision electro-optical tracking system.

Wei Tong1, Tao Zhao1, Qianwen Duan2

  • 1College of Electrical Engineering, Sichuan University, Chendu 610065, China.

ISA Transactions
|March 22, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces two non-singleton interval type-2 fuzzy PID controllers to enhance electro-optical tracking systems. These novel controllers demonstrate superior anti-interference capabilities compared to existing methods.

Keywords:
Electro-optical tracking systemImproved QPSO with adaptive coefficientsNon-singleton interval type-2 fuzzy PID controllersStep disturbance and sinusoidal disturbance

More Related Videos

A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

15.1K
Automated Delivery of Microfabricated Targets for Intense Laser Irradiation Experiments
06:40

Automated Delivery of Microfabricated Targets for Intense Laser Irradiation Experiments

Published on: January 28, 2021

4.5K

Related Experiment Videos

Last Updated: Nov 12, 2025

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

8.8K
A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

15.1K
Automated Delivery of Microfabricated Targets for Intense Laser Irradiation Experiments
06:40

Automated Delivery of Microfabricated Targets for Intense Laser Irradiation Experiments

Published on: January 28, 2021

4.5K

Area of Science:

  • Control Systems Engineering
  • Fuzzy Logic Systems
  • Robotics and Automation

Background:

  • High-precision electro-optical tracking systems (ETS) require robust anti-interference capabilities.
  • Traditional PID controllers often struggle with complex disturbances.
  • Interval type-2 fuzzy logic offers enhanced uncertainty handling compared to type-1 systems.

Purpose of the Study:

  • To develop and evaluate novel non-singleton interval type-2 fuzzy PID (NIT2F-PID) controllers for ETS.
  • To improve the anti-interference performance of ETS.
  • To compare the effectiveness of different fuzzifier types and optimization algorithms.

Main Methods:

  • Design of two NIT2F-PID controllers: N1IT2F-PID (using type-1 fuzzifier) and N2IT2F-PID (using type-2 fuzzifier).
  • Optimization of controller parameters using Particle Swarm Optimization (PSO), Quantum-behaved PSO (QPSO), Weighted QPSO (WQPSO), and an improved LTQPSO.
  • Comparative analysis against PID, singleton T1 fuzzy PID (ST1F-PID), singleton interval T2 fuzzy PID (SIT2F-PID), T1 non-singleton interval T2 fuzzy (N1IT2F), and T2 non-singleton interval T2 fuzzy (N2IT2F) controllers.
  • Testing under step and sinusoidal disturbances.

Main Results:

  • The proposed NIT2F-PID controllers exhibited superior performance in terms of anti-interference ability.
  • N2IT2F-PID and N1IT2F-PID controllers showed significant improvements over all other tested controllers.
  • Comparative analysis confirmed the effectiveness of the chosen optimization algorithms in tuning controller parameters.

Conclusions:

  • Non-singleton interval type-2 fuzzy PID controllers offer a significant advancement for high-precision electro-optical tracking systems.
  • The use of type-2 fuzzifiers in non-singleton systems enhances robustness against disturbances.
  • The developed controllers provide a more effective solution for demanding tracking applications.