Tuning of SMC Parameters for Robotic Manipulator Based on Whale Optimization Algorithm

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Abstract

A 2-link robotic manipulator is selected as a research instance, a sliding mode control(SMC) law is designed. Parameters tuning of sliding mode controller is converted to a nonlinear optimization problem with the objects of minimizing the trajectory tracking error and eliminating chattering of the control torques. The whale optimization algorithm (WOA) is adopted in this paper to obtain the best parameters of controller, and a comparative study with the results that are searched by particle swarm optimization (PSO) is made. Through simulation of the manipulator, control effects of the parameters obtained by the two optimization methods are compared. Research shows that WOA is a viable optimization method for parameter tuning of sliding mode control of robotic manipulator, and the optimization model proposed in this paper can effectively eliminate the chattering problem of control torques.

Original languageEnglish
Title of host publicationWRC SARA 2019 - World Robot Conference Symposium on Advanced Robotics and Automation 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages248-253
Number of pages6
ISBN (Electronic)9781728155524
DOIs
StatePublished - Aug 2019
Event2nd World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2019 - Beijing, China
Duration: 21 Aug 2019 → …

Publication series

NameWRC SARA 2019 - World Robot Conference Symposium on Advanced Robotics and Automation 2019

Conference

Conference2nd World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2019
Country/TerritoryChina
CityBeijing
Period21/08/19 → …

Keywords

  • Nonlinear Optimization
  • Robotic Manipulator Control
  • Sliding Mode Control
  • Whale Optimization Algorithm

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