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

180
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...
180
PD Controller: Design01:26

PD Controller: Design

353
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,...
353
PI Controller: Design01:24

PI Controller: Design

503
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...
503
Transmission Shafts: Problem Solving01:09

Transmission Shafts: Problem Solving

291
Designing a solid shaft that transmits power from a motor to a machine tool involves a series of calculations to ensure the shaft can withstand the stresses applied by bending moments and torques. First, calculate the torque exerted on the gear, considering the power transmitted by the shaft and its rotational speed. Following this, compute the tangential forces acting on the gears, which directly relate to the torque and the gear radius.
Next, use bending moment diagrams for the shaft to...
291
Multimachine Stability01:25

Multimachine Stability

230
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
230
Load-frequency control01:28

Load-frequency control

260
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
260

You might also read

Related Articles

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

Sort by
Same author

Trajectory Planning Method for a Robotic Arm Based on an Improved Multi-Objective Golden Jackal Optimization Algorithm.

Sensors (Basel, Switzerland)·2026
Same author

Optimized Design of a Sub-Arc-Second Micro-Drive Rotary Mechanism Based on the Swarm Optimization Algorithm.

Micromachines·2025
Same author

Optimization Design of the Two-Stage Reduction Micro-Drive Mechanism Based on Particle Swarm Algorithm.

Micromachines·2025
Same author

Analysis of Serum IgG1 to Predict Progression and Therapeutic Effect in Patients with Multiple Myeloma.

Journal of oncology·2022
Same author

Long-term maternal intake of inulin exacerbated the intestinal damage and inflammation of offspring rats in a DSS-induced colitis model.

Food & function·2022
Same author

Direct imaging of the disconnection climb mediated point defects absorption by a grain boundary.

Nature communications·2022
Same journal

Correction: Kang et al. Fluid Flow to Electricity: Capturing Flow-Induced Vibrations with Micro-Electromechanical-System-Based Piezoelectric Energy Harvester. <i>Micromachines</i> 2024, <i>15</i>, 581.

Micromachines·2026
Same journal

Femtosecond Laser Texturing of Wood Coatings with Bio-Based Epoxy and Wax Additives for Enhanced Hydrophobicity.

Micromachines·2026
Same journal

Engineering of Optoelectronic Devices for Renewable Energy Applications.

Micromachines·2026
Same journal

Phase Transformation and Electrochemical Behavior of Hexagonal TiO<sub>2</sub> Nanotubes Under Different Annealing Temperatures and Heating Rates.

Micromachines·2026
Same journal

Process Optimization and Predictive Modeling of Femtosecond Laser Precision Milling for Commercial PMMA Slices.

Micromachines·2026
Same journal

A Hybrid Preprocessing Multi-Objective Surrogate Model for Thermal MEMS Actuators.

Micromachines·2026
See all related articles

Related Experiment Video

Updated: Sep 13, 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 Error Modeling and Predictive Compensation for Direct-Drive Turntables Based on CEEMDAN-TPE-LightGBM-APC

Manzhi Yang1, Hao Ren1, Shijia Liu1

  • 1College of Mechanical Engineering, Xi'an University of Science and Technology, No. 58 Yanta Middle Road, Xi'an 710054, China.

Micromachines
|July 30, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a novel dynamic error compensation model for direct-drive turntables, significantly improving positioning accuracy through advanced decomposition and machine learning prediction techniques for precision mechanical systems.

Keywords:
LightGBMadaptive correctiondirect-drive turntablepositioning errorpredictive compensation

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
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

1.8K

Related Experiment Videos

Last Updated: Sep 13, 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
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

1.8K

Area of Science:

  • Mechanical Engineering
  • Control Systems Engineering
  • Signal Processing

Background:

  • Direct-drive turntables are crucial for high-precision macro-micro drive systems.
  • Positioning accuracy of these turntables is paramount for overall system performance.
  • Accurate error prediction and compensation are essential for advanced control strategies.

Purpose of the Study:

  • To develop a dynamic continuous error compensation model for direct-drive turntables.
  • To enhance the positioning accuracy of direct-drive turntables.
  • To enable online prediction and correction of positioning errors.

Main Methods:

  • A "decomposition-modeling-integration-correction" strategy was employed.
  • Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) decomposed historical error data.
  • Tree-structured Parzen Estimator (TPE)-optimized Light Gradient Boosting Machine (LightGBM) models predicted component errors, followed by Adaptive Prediction Correction (APC).

Main Results:

  • Compensated positioning error ranges were significantly reduced on both test and extrapolation test sets.
  • Standard deviations of positioning errors were reduced by 71.2% (test set) and 61.6% (extrapolation test set).
  • The model demonstrated high flexibility, adaptability, and online prediction-correction capabilities.

Conclusions:

  • The proposed dynamic continuous error compensation model effectively enhances the accuracy of direct-drive turntables.
  • The method maintains prediction stability and operational efficiency.
  • This research holds significant theoretical and practical value for error compensation in precision mechanical systems.