Supercharge Your Innovation With Domain-Expert AI Agents!

An Estimation Algorithm for Dynamic Parameters of Force Feedback Devices Based on Particle Swarm Optimization

A technology of dynamic parameters and particle swarm algorithm, applied in the direction of instruments, adaptive control, control/regulation system, etc., can solve problems such as poor effect and large torque error

Active Publication Date: 2021-01-19
NANCHANG UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the estimated torque error is large, the effect of parameter estimation is poor, and it is easier to fall into local optimum

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • An Estimation Algorithm for Dynamic Parameters of Force Feedback Devices Based on Particle Swarm Optimization
  • An Estimation Algorithm for Dynamic Parameters of Force Feedback Devices Based on Particle Swarm Optimization
  • An Estimation Algorithm for Dynamic Parameters of Force Feedback Devices Based on Particle Swarm Optimization

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045] The invention will be further illustrated by the following examples.

[0046] Step 1: Set the ideal trajectory of the joint angle of the force feedback device;

[0047] The force feedback device has 3 rotatable joints J 1 、J 2 、J 3 , the corresponding three joint angles are θ 1 , θ 2 , θ 3 . The ideal motion trajectories for setting the three joint angles are: angle θ 1 (t), θ 2 (t), θ 3 (t), angular velocity angular acceleration details as follows:

[0048] Angle: θ 1 =0.5sint θ 2 =0.5sint θ 3 =0.2sint

[0049] Angular velocity:

[0050] Angular acceleration:

[0051] Step 2: Track the position of the ideal motion trajectory of the joint angle;

[0052] Use the PID control algorithm to control the three joints of the force feedback device to track the ideal trajectory, and obtain the input torque τ of the three joints 1 , τ 2 , τ 3 and angle θ 1 (t), θ 2 (t), θ 3 (t). Obtaining the Angular Velocity of Each Joint Using Nonlinear ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a force feedback equipment kinetic parameter estimation algorithm based on a particle swarm algorithm. Specifically, an improved comprehensive learning particle swarm algorithmis used for better estimating the kinetic parameters of the force feedback equipment. The algorithm mainly comprises the following steps: step 1, setting an ideal motion trail of a joint angle of force feedback equipment; step 2, performing position tracking on the ideal motion trail of the joint angle; step 3, sampling a joint angle movement track and an input torque; and step 4, estimating the parameters of the force feedback equipment by utilizing an ICLPSO algorithm. According to the method, four strategies, namely a hierarchical updating strategy, a position learning strategy, a guide particle learning strategy and a global optimal learning strategy, are used, so that the problems of two-step forward and one-step backward and the premature problem in the traditional PSO algorithm areeffectively solved. Compared with a traditional PSO algorithm, the ICLPSO algorithm is higher in convergence speed, the obtained model parameters are more accurate, accurate torque estimation values can be provided for all joints, and the performance of the control algorithm is improved.

Description

technical field [0001] The invention relates to the estimation of parameters of force feedback equipment, in particular to an estimation algorithm of dynamic parameters of force feedback equipment based on particle swarm algorithm. Background technique [0002] Due to the prominent position of haptics in human perception, researchers have tried to introduce haptic characteristics into teleoperated robots, virtual reality and other research fields to provide haptic feedback information for operators in the process of human-computer interaction. For example, when an accident occurs in a nuclear power plant, it is necessary to complete tasks such as detection and maintenance through teleoperated robots. At this time, video surveillance is facing serious interference. The operator can effectively improve the accuracy and reliability of the operation with the help of tactile feedback information. In virtual surgery, doctors conduct real-time surgical simulation training on a virt...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 李春泉何永华杨峰
Owner NANCHANG UNIV
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com