PARALLEL PLATFORM CONTROLLER BASED ON ADAPTIVE DIFFERENCE ALGORITHM – PART 1

Authors

  • RUIYANG WANG School of Automation, University of Electronic Science and Technology of China, Chengdu 610054 China. Author
  • QIUXIANG GU School of Automation, University of Electronic Science and Technology of China, Chengdu, 610054, China. Author
  • SIYU LU School of Automation, University of Electronic Science and Technology of China, Chengdu 610054 China. Author
  • JIAWEI TIAN School of Automation, University of Electronic Science and Technology of China, Chengdu 610054 China. Author
  • ZHENGTONG YIN College of Resource and Environment Engineering, Guizhou University, Guiyang 550025, China. Author
  • XIAOLU LI School of Geographical Sciences, Southwest University, Chongqing, 400715, China. Author
  • XIAOBING CHEN Division of Electrical and Computer Engineering, Louisiana State University, Baton Rouge 70803 LA, USA. Author
  • LIRONG YIN Department of Geography and Anthropology, Louisiana State University, Baton Rouge 70803 LA, USA. Author
  • WENFENG ZHENG School of Automation, University of Electronic Science and Technology of China, Chengdu 610054 China. Author

DOI:

https://doi.org/10.59277/RRST-EE.2024.2.21

Keywords:

Workspace control, Model predictive controller (MPC), Adaptive difference algorithm, Parallel platform control

Abstract

There are two main approaches to motion control on parallel platforms: joint space control and workspace control. Joint space control is an easy-to-implement semi-closed-loop strategy, but its control effect could be better. The workspace control is to obtain the real-time position of the parallel platform through the forward solution and close the speed and position loop of the parallel platform in the workspace. This paper uses a model predictive controller (MPC) to control the parallel platform with workspace control as the research goal. The loss function is constructed based on the swarm intelligence optimization idea, and the adaptive difference algorithm is used to optimize the parameters of MPC. This part details the research background and the algorithm design process. Then, the MPC algorithm is implemented on the upper computer using C++, and the physical test is implemented. The test results show that the controller has a good control effect on the physical platform.

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Published

07.07.2024

Issue

Vol. 69 No. 2 (2024): RRST-EE

Section

Automatique et ordinateurs | Automation and Computer Sciences

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Copyright (c) 2024 REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE

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How to Cite

PARALLEL PLATFORM CONTROLLER BASED ON ADAPTIVE DIFFERENCE ALGORITHM – PART 1. (2024). REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE, 69(2), 243-254. https://doi.org/10.59277/RRST-EE.2024.2.21