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Point stabilization of mobile robots by genetic sliding mode approach with neural dynamics model on uneven surface

  • Zhengcai Cao*
  • , Yingtao Zhao
  • , Yili Fu
  • *Corresponding author for this work
  • Beijing University of Chemical Technology
  • Harbin Institute of Technology

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

Abstract

In this work, a novel point stabilization control strategy for mobile robots which moves on uneven surface is presented. Firstly, sliding mode method is adopted to extend the nonlinear kenimatic control law to dynamic system, so that the robot is driven by torques. Then, to solve the speed and torque jump problem, the neural dynamics model is integrated into the presented controller. In addition, we utilize genetic algorithm (GA) to optimize the controller parameters for obtaining better stabilization performance. The stability of the proposed control system is analyzed by using Lyapunov theory. Finally, simulation results are given to illustrate the effectiveness of the proposed control scheme.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Automation Science and Engineering
Subtitle of host publicationGreen Automation Toward a Sustainable Society, CASE 2012
Pages1150-1155
Number of pages6
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 IEEE International Conference on Automation Science and Engineering: Green Automation Toward a Sustainable Society, CASE 2012 - Seoul, Korea, Republic of
Duration: 20 Aug 201224 Aug 2012

Publication series

NameIEEE International Conference on Automation Science and Engineering
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference2012 IEEE International Conference on Automation Science and Engineering: Green Automation Toward a Sustainable Society, CASE 2012
Country/TerritoryKorea, Republic of
CitySeoul
Period20/08/1224/08/12

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