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...

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...

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,...

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...

Time-Domain Interpretation of PD Control

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...

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

IMC based modified Smith predictor for second order delay dominated processes with RHP.

ISA transactions·2023

Same author

Simple internal model control based modified Smith predictor for integrating time delayed processes with real-time verification.

ISA transactions·2021

Same author

Prediction of protein secondary structure using probability based features and a hybrid system.

Journal of bioinformatics and computational biology·2013

Same author

A simple nonlinear PD controller for integrating processes.

ISA transactions·2013

Same author

Performance improvement of PI controllers through dynamic set-point weighting.

ISA transactions·2010

Same author

An improved auto-tuning scheme for PI controllers.

ISA transactions·2007

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

Search research articles

Related Experiment Video

Updated: Jun 21, 2026

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

An improved auto-tuning scheme for PID controllers.

Chanchal Dey¹, Rajani K Mudi

¹Department of Applied Physics, University of Calcutta, 92 A.P.C. Road, Kolkata, India. chanchaldey@yahoo.co.in

ISA Transactions

|August 4, 2009

Summary

This summary is machine-generated.

This study introduces an improved auto-tuning method for Ziegler-Nichols PID controllers, significantly reducing overshoots in complex processes. The new augmented ZNPID (AZNPID) offers enhanced stability and robust performance for real-time applications.

More Related Videos

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

Related Experiment Videos

Last Updated: Jun 21, 2026

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

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

Area of Science:

Control Engineering
Automation Systems
Process Control

Background:

Ziegler-Nichols tuned PID controllers (ZNPIDs) often exhibit large overshoots, limiting their use in high-order and nonlinear systems.
Existing auto-tuning methods may not adequately address performance limitations in complex industrial processes.

Purpose of the Study:

To develop an enhanced auto-tuning scheme for PID controllers that overcomes the overshoot limitations of traditional Ziegler-Nichols tuning.
To generalize and extend previous auto-tuning work to a wider range of processes, including nonlinear and high-order systems.

Main Methods:

An augmented ZNPID (AZNPID) scheme is proposed, integrating heuristic rules and an online gain modifying factor based on process states.
The method builds upon prior research on auto-tuning for PI controllers, adapting it for ZNPIDs.
Performance evaluation involved testing on various high-order linear and nonlinear dead-time processes.

Main Results:

The AZNPID scheme demonstrated improved performance compared to standard ZNPID, refined ZNPID (RZNPID), and other existing methods.
Stability was addressed for linear processes, and robust performance was observed across parameter variations and dead-time changes.
The proposed scheme was successfully implemented on a real-time servo-based position control system.

Conclusions:

The augmented ZNPID (AZNPID) provides a more generalized and effective auto-tuning solution for PID controllers, particularly for challenging processes.
The heuristic-based online gain modification enhances controller performance and robustness, making it suitable for practical applications.