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

Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

148
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...
148
PD Controller: Design01:26

PD Controller: Design

293
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,...
293
Second Order systems II01:18

Second Order systems II

137
In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
137
Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

167
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...
167
Feedback control systems01:26

Feedback control systems

352
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...
352
Transient and Steady-state Response01:24

Transient and Steady-state Response

221
In control systems, test signals are essential for evaluating performance under various conditions. The ramp function is effective for systems undergoing gradual changes, while the step function is suitable for assessing systems facing sudden disturbances. For systems subjected to shock inputs, the impulse function is the most appropriate test signal.
These test signals are integral in designing control systems to exhibit two key performance aspects: transient response and steady-state...
221

You might also read

Related Articles

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

Sort by
Same author

The role of long non-coding RNA HCP5 in ulcerative cutaneous tuberculosis therapy introduction.

Frontiers in cellular and infection microbiology·2026
Same author

Adaptive PD-Like Event-Triggered Secure Synchronization Control for Inertial Neural Networks and Signal Encryption Application.

IEEE transactions on cybernetics·2026
Same author

Anti-Disturbance Intermediate Observer-Based Fault Estimation and Fault-Tolerant Control for Markovian Jump Systems.

IEEE transactions on cybernetics·2026
Same author

A Zinc Finger Protein-Based Prognostic Model in Lung Adenocarcinoma Identifies FGD3 as a Marker Associated with Lorlatinib Resistance.

Cancers·2026
Same author

Bufalin post-transcriptionally suppresses STAT3 to alleviate renal ferroptosis and tubulointerstitial fibrosis in diabetic kidney disease.

Renal failure·2026
Same author

Comparative analysis and influential factors of embodied carbon emissions across low-rise, multi-story, and high-rise residential buildings in China.

Scientific reports·2026

Related Experiment Video

Updated: Jul 27, 2025

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

13.8K

Dynamic Threshold Finite-Time Prescribed Performance Control for Nonlinear Systems With Dead-Zone Output.

Xin Liu, Huaguang Zhang, Jiayue Sun

    IEEE Transactions on Cybernetics
    |June 6, 2023
    PubMed
    Summary

    This study introduces an adaptive control strategy for nonlinear systems with dead zones, utilizing a dynamic event-triggered approach to enhance resource efficiency. The novel method ensures bounded system signals and reduces computational complexity.

    More Related Videos

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
    08:18

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

    Published on: August 15, 2020

    5.0K
    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

    2.5K

    Related Experiment Videos

    Last Updated: Jul 27, 2025

    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

    13.8K
    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
    08:18

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

    Published on: August 15, 2020

    5.0K
    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

    2.5K

    Area of Science:

    • Control Systems Engineering
    • Nonlinear Dynamics
    • Robotics and Automation

    Background:

    • Nonlinear systems present significant challenges in control engineering.
    • The dead-zone phenomenon complicates precise tracking control.
    • Existing control methods may suffer from computational complexity and inefficient resource utilization.

    Purpose of the Study:

    • To develop an adaptive tracking control strategy for nonlinear systems with dead zones.
    • To introduce a novel dynamic threshold scheme for improved performance and efficiency.
    • To mitigate computational complexity using a command filter backstepping approach.

    Main Methods:

    • An adaptive model incorporating a Nussbaum function to address the dead-zone.
    • A dynamic threshold scheme combining continuous and finite-time performance functions.
    • A dynamic event-triggered strategy and command filter backstepping.

    Main Results:

    • The proposed control strategy effectively handles the dead-zone phenomenon.
    • The dynamic event-triggered approach reduces data transmission and improves resource utilization.
    • The command filter backstepping prevents computational complexity explosion, ensuring bounded system signals.

    Conclusions:

    • The novel adaptive control strategy is effective for nonlinear systems with dead zones.
    • The dynamic event-triggered mechanism enhances control system efficiency.
    • The approach guarantees system stability and boundedness of all signals.