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Adaptive NN-based tracking control for partial uncertain time-delayed WMR system

  • Harbin Institute of Technology
  • Tangshan Normal University

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

Abstract

In this paper, an adaptive neural network (NN)-based tracking control algorithm is proposed for the partial uncertain state time-delayed wheeled mobile robotic (WMR) system with. By using the backstepping method, and the appropriate Lyapunov-Krasovskii functionals, a suitable adaptive controllers is designed for the WMR system such that 1) eliminate the influence of partial uncertain time delay on system stability; 2) ensure all signals in WMR system to be bounded; 3) guarantee the robot can track the desired trajectory with the error convergence to a compact set by zero. The numerical simulation results verify the performance of the proposed control algorithm. Keywords-Adaptive control, neural network, partial time delay, wheeled mobile robot, Lyapunov function.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages118-123
Number of pages6
ISBN (Electronic)9781538668689
DOIs
StatePublished - 2 Jul 2018
Event2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018 - Kandima, Maldives
Duration: 1 Aug 20185 Aug 2018

Publication series

Name2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018

Conference

Conference2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018
Country/TerritoryMaldives
CityKandima
Period1/08/185/08/18

Keywords

  • Adaptive control
  • Lyapunov function
  • neural network
  • partial time delay
  • wheeled mobile robot

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