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Research on Optimization of Control Parameters of Coal Sampling Robot Based on Model and Neural Network Algorithm

  • Xiaodong Liu
  • Haibo XuEmail author
  • Jun Wang
  • Rui Wang
  • Li Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11745)

Abstract

This paper takes the single joint (big arm joint) servo control system of coal sampling robot as the research object, analyzes the structure of servo control system, establishes the model of single joint servo control system to study the method of tuning and optimizing the control parameters of the servo system. The combination of model-based control parameter tuning and improved BP neural network control parameter optimization is adopted to improve the system’s ability to adapt to the load and improve the performance of system.

Keywords

Load inertia BP neural network Control parameter optimization 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Xiaodong Liu
    • 1
  • Haibo Xu
    • 1
    Email author
  • Jun Wang
    • 2
  • Rui Wang
    • 1
  • Li Liu
    • 1
  1. 1.Xi’an Jiaotong UniversityXi’anChina
  2. 2.Xi’an Hongyu Mining Special Mobile Equipment Co.Xi’anChina

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