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

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...
Open and closed-loop control systems01:17

Open and closed-loop control systems

Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal and...
Feedback control systems01:26

Feedback control systems

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...
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length, the...
Transfer Function in Control Systems01:21

Transfer Function in Control Systems

The transfer function is a fundamental concept in the analysis and design of linear time-invariant (LTI) systems. It offers a concise way to understand how a system responds to different inputs in the frequency domain. It serves as a bridge between the time-domain differential equations that describe system dynamics and the frequency-domain representation that facilitates easier manipulation and analysis.
To derive the transfer function, consider a general nth-order linear time-invariant...
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.

You might also read

Related Articles

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

Sort by
Same author

A Lightweight Temporal Convolutional Network for Contactless SPPB-Aligned Functional Fall-Risk Stratification in Older Adults Using Monocular RGB Video.

Sensors (Basel, Switzerland)·2026
Same author

AI-Assisted Dynamic Postural Control Screening to Improve Functional Mobility in Older Adult Populations: Quasi-Experimental Study.

JMIR aging·2025
Same author

Backstepping fuzzy-neural-network control design for hybrid maglev transportation system.

IEEE transactions on neural networks and learning systems·2015
Same author

Fuzzy-neural-network inherited sliding-mode control for robot manipulator including actuator dynamics.

IEEE transactions on neural networks and learning systems·2014
Same author

Adaptive fuzzy neural network control design via a T-S fuzzy model for a robot manipulator including actuator dynamics.

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

Cascade direct adaptive fuzzy control design for a nonlinear two-axis inverted-pendulum servomechanism.

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

Related Experiment Video

Updated: Jul 7, 2026

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

Robust control for nonlinear motor-mechanism coupling system using wavelet neural network.

Rong-Jong Wai1

  • 1Dept. of Electr. Eng., Yuan Ze Univ., Chung-li, Taiwan.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|February 2, 2008
PubMed
Summary
This summary is machine-generated.

This study presents a robust control system for permanent magnet synchronous servo motors in toggle mechanisms. The system uses a wavelet neural network to adapt to uncertainties, ensuring stable performance against disturbances.

More Related Videos

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Related Experiment Videos

Last Updated: Jul 7, 2026

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

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Area of Science:

  • Robotics and Control Systems
  • Mechanical Engineering
  • Artificial Intelligence

Background:

  • Toggle mechanisms driven by permanent magnet synchronous servo motors are crucial in various applications.
  • Existing control methods often struggle with uncertainties and external disturbances.
  • Developing robust control strategies is essential for reliable operation.

Purpose of the Study:

  • To design and validate a robust control system for a permanent magnet synchronous servo motor-driven toggle mechanism.
  • To enhance the adaptability and resilience of the control system against uncertainties.
  • To improve the positional accuracy and dynamic stability of the motor-mechanism system.

Main Methods:

  • Computed torque control principles were applied to develop a position controller.
  • A wavelet neural network (WNN) uncertainty observer was integrated to adaptively estimate lumped uncertainties online.
  • A robust control system combining computed torque control, WNN uncertainty observer, and a compensated controller was formulated based on Lyapunov stability theory.

Main Results:

  • Simulated and experimental results demonstrated the effectiveness of the proposed control system.
  • The system exhibited robust dynamic behaviors under parametric variations.
  • The control strategy successfully mitigated the effects of external disturbances.

Conclusions:

  • The proposed robust control system effectively controls the position of the motor-mechanism coupling system.
  • The integration of a WNN uncertainty observer enhances the system's robustness against uncertainties.
  • The developed control strategy offers a reliable solution for precise and stable operation of permanent magnet synchronous servo motor-driven toggle mechanisms.