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

Frictional Forces on Flat Belts01:28

Frictional Forces on Flat Belts

1.4K
Flat belts are commonly used in various industrial applications for transmitting power from one pulley to another. When a flat belt is wrapped around a set of pulleys, it experiences different tensions at the driving pulley ends due to the friction between the belt and pulley surface. When the pulley moves in a counterclockwise direction, the tension T2 on the opposite side of the pulley where the belt is moving away from is higher than the tension T1 on the side where the belt is moving...
1.4K
Two-Dimensional Force System01:20

Two-Dimensional Force System

1.6K
A two-dimensional system in mechanical engineering involves the analysis of motion and forces in a plane. A two-dimensional force vector can be resolved into its components as:
1.6K
Three-Dimensional Force System01:30

Three-Dimensional Force System

2.8K
In mechanical engineering, a three-dimensional force system is a system of forces acting in three dimensions, with forces applied along the x, y, and z coordinate axes. The three-dimensional force system is an important concept in mechanical engineering, as it allows engineers to understand and analyze the behavior of objects and structures in three dimensions. By understanding the forces acting on a system, engineers can design more efficient and effective mechanical systems that can withstand...
2.8K
Power Expended by a Constant Force00:57

Power Expended by a Constant Force

9.0K
The relationship between work done and the time taken to do it can be explained using the concept of power. For example, several sprinters in a race may have the same velocity when they reach the finish line, therefore doing the same amount of work, but the winner does it in the least amount of time. Thus, power is defined as the rate of doing work. Since work can vary as a function of time, the average power is defined as the work done during a time interval, divided by the time interval.
9.0K
Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

1.3K
Solving problems related to two-dimensional force systems is an essential aspect of mechanics and engineering. By applying the principles of vector analysis and force equilibrium, one can determine the effect of multiple forces acting on an object in a two-dimensional space.
The first step to solving a two-dimensional force system problem is to draw a free-body diagram of the object under consideration. This diagram helps identify all the external forces acting on the object, including their...
1.3K
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

1.4K
A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
1.4K

You might also read

Related Articles

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

Sort by
Same author

Real-time laser stripe robust detection for robotic weld seam tracking based on temporal image sequences.

Applied optics·2026
Same author

Activation of the RAS/PPARα pathway reduces backfat deposition of Gayal (Bos frontalis).

BMC genomics·2026
Same author

Superior correlation with clinical activity and unique detection patterns: a prospective study of FAPI versus FDG-PET in polymyalgia rheumatica and giant cell arteritis.

European journal of nuclear medicine and molecular imaging·2026
Same author

Distinct immune activation patterns in adult-onset Still's disease with fungal infections.

Frontiers in immunology·2026
Same author

Structural insights into the gating mechanism of the fission yeast phosphate exporter SpXpr1.

Cell discovery·2026
Same author

Mechanistic insights into ligand selectivity in <i>μ</i>- and <i>δ</i>-opioid receptors beyond the "message-address" conceptual framework.

Acta pharmaceutica Sinica. B·2026
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Jan 26, 2026

Molecular Spring Constant Analysis by Biomembrane Force Probe Spectroscopy
08:10

Molecular Spring Constant Analysis by Biomembrane Force Probe Spectroscopy

Published on: November 20, 2021

3.4K

An Adaptive Sliding-Mode Iterative Constant-force Control Method for Robotic Belt Grinding Based on a One-Dimensional

Tie Zhang1, Ye Yu2, Yanbiao Zou3

  • 1School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510000, China. merobot@scut.edu.cn.

Sensors (Basel, Switzerland)
|April 10, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces an adaptive iterative constant-force control for robotic belt grinding. The method enhances processing quality and efficiency by reducing force fluctuations and improving surface finish.

Keywords:
abrasive belt grindingadaptive sliding-mode controlconstant-force controliterative learningrobot

More Related Videos

Force-Clamp Rheometry for Characterizing Protein-based Hydrogels
09:55

Force-Clamp Rheometry for Characterizing Protein-based Hydrogels

Published on: August 21, 2018

7.4K
Measurement of Dynamic Force Acted on Water Strider Leg Jumping Upward by the PVDF Film Sensor
07:17

Measurement of Dynamic Force Acted on Water Strider Leg Jumping Upward by the PVDF Film Sensor

Published on: August 3, 2018

6.4K

Related Experiment Videos

Last Updated: Jan 26, 2026

Molecular Spring Constant Analysis by Biomembrane Force Probe Spectroscopy
08:10

Molecular Spring Constant Analysis by Biomembrane Force Probe Spectroscopy

Published on: November 20, 2021

3.4K
Force-Clamp Rheometry for Characterizing Protein-based Hydrogels
09:55

Force-Clamp Rheometry for Characterizing Protein-based Hydrogels

Published on: August 21, 2018

7.4K
Measurement of Dynamic Force Acted on Water Strider Leg Jumping Upward by the PVDF Film Sensor
07:17

Measurement of Dynamic Force Acted on Water Strider Leg Jumping Upward by the PVDF Film Sensor

Published on: August 3, 2018

6.4K

Area of Science:

  • Robotics
  • Manufacturing Engineering
  • Control Systems

Background:

  • Robotic belt grinding requires precise force control for quality and efficiency.
  • Existing methods struggle with grinding force uncertainties and dynamic variations.
  • A one-dimension force sensor limits traditional force control approaches.

Purpose of the Study:

  • To develop an adaptive sliding-mode iterative constant-force control for a 6-DOF robotic belt grinding platform.
  • To address uncertainties in grinding forces and improve control system stability.
  • To enhance the processing quality and efficiency of robotic belt grinding operations.

Main Methods:

  • Revealed the relationship between normal and tangential grinding forces, presenting a simplified mapping for 1D sensors.
  • Established a deformation-based dynamic model for robotic belt grinding.
  • Proposed an adaptive iterative learning method combined with sliding mode control.

Main Results:

  • Reduced grinding force fluctuation to less than 2N after ten iterations.
  • Significantly decreased the mean, standard deviation, and variance of absolute grinding force error.
  • Demonstrated significant improvement in the surface quality of machined parts.

Conclusions:

  • The proposed force control method is effective for robotic belt grinding.
  • The adaptive algorithm exhibits fast convergence and strong adaptability.
  • This approach enhances both processing precision and efficiency in automated manufacturing.