Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

PID Controller

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...

Time and frequency -Domain Interpretation of PI Control

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...

PD Controller: Design

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,...

Phase-lead and Phase-lag Controllers

Phase-lead and Phase-lag Controllers

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 filters, manage...

PI Controller: Design

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 Configurations

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...

You might also read

Related Articles

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

Sort by

Same author

Simulation of fruit-set and trophic competition and optimization of yield advantages in six Capsicum cultivars using functional-structural plant modelling.

Annals of botany·2010

Same author

Analysis of direct action fuzzy PID controller structures.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2008

Same author

Persistent infection of mice by lactate dehydrogenase-elevating virus: effects of immunosuppression on virus replication and antiviral immune responses.

Virus research·1989

Same author

An intelligent end-effector for a rehabilitation robot.

Journal of medical engineering & technology·1989

Search research articles

Related Experiment Video

Updated: Jul 7, 2026

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

Two-level tuning of fuzzy PID controllers.

G I Mann¹, B G Hu, R G Gosine

¹Centre for Cold Ocean Resources Eng., Memorial Univ. of Newfoundland, St. John's, Nfld.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|February 5, 2008

Summary

This study introduces a two-stage fuzzy PID tuning method, combining nonlinear high-level and linear low-level tuning for enhanced fuzzy control performance. The approach simplifies fuzzy systems and uses tuning diagrams for effective control applications.

More Related Videos

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

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

Related Experiment Videos

Last Updated: Jul 7, 2026

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

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

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

Area of Science:

Control Engineering
Computational Intelligence
Automation Systems

Background:

Traditional Proportional-Integral-Derivative (PID) controllers offer linear control but struggle with complex nonlinear systems.
Fuzzy logic controllers (FLC) provide nonlinear control capabilities but often require intricate tuning processes.
A systematic and efficient tuning methodology for fuzzy PID controllers is essential for practical implementation.

Purpose of the Study:

To propose a novel two-stage tuning method for fuzzy PID controllers, integrating both nonlinear and linear tuning phases.
To develop a simplified fuzzy system model suitable for two-point control applications.
To demonstrate the effectiveness of the proposed tuning method through various applications.

Main Methods:

Defining and simplifying fuzzy systems for two-point control.
Constructing non-linearity tuning diagrams for high-level fuzzy system tuning.
Deducing linear tuning parameters from conventional PID knowledge for low-level tuning.
Developing high-level tuning heuristics based on the constructed tuning diagrams.

Main Results:

The proposed method successfully determines both nonlinear and linear characteristics of the fuzzy output.
Tuning diagrams facilitate a structured approach to high-level tuning.
Heuristics derived from tuning diagrams simplify the tuning process.
Demonstrated validity across different applications, showcasing robust fuzzy control.

Conclusions:

The presented two-stage fuzzy PID tuning method offers an effective approach to achieve optimal fuzzy control performance.
The integration of nonlinear and linear tuning stages addresses the complexities of fuzzy system parameterization.
The method provides a practical framework for implementing advanced fuzzy PID controllers in real-world systems.