An Actuator Based on Linkage Structure and Control System Design

Yucan Huang*, Dingji Luo, Fang Wang, Xueshan Gao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A robot system based on a linkage structure, which can precisely perceive the working state by utilizing a variety of sensors carried on board. A multi-sensor data fusion strategy to integrate more accurate data based on different working states of the robot, thereby enhancing the robot's capabilities in receiving commands and perceiving the environment. Furthermore, at the control level, a neural network control based on radial basis functions is applied to the robot. This algorithm leverages the approximation properties of neural networks to estimate disturbances and uncertainties in the nonlinear system of the robot more accurately, enabling smoother and faster control. Experimental validation demonstrates that the utilization of neural network control on this robot yields superior control performance compared to traditional PID control, affirming its high operational efficiency.

Original languageEnglish
Title of host publication2024 IEEE International Conference on Mechatronics and Automation, ICMA 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1050-1055
Number of pages6
ISBN (Electronic)9798350388060
DOIs
Publication statusPublished - 2024
Event21st IEEE International Conference on Mechatronics and Automation, ICMA 2024 - Tianjin, China
Duration: 4 Aug 20247 Aug 2024

Publication series

Name2024 IEEE International Conference on Mechatronics and Automation, ICMA 2024

Conference

Conference21st IEEE International Conference on Mechatronics and Automation, ICMA 2024
Country/TerritoryChina
CityTianjin
Period4/08/247/08/24

Keywords

  • Data fusion
  • Neural network control
  • Robot arm system

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