Trajectory Tracking based on Adaptive Weights Receding Horizon Control by Differential Drive Robot

Samidha Mridul Verma, Rahul Ravichandran, Rahul Singhal, Rajesh Kumar

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

1 Citation (Scopus)

Abstract

In this paper, an adaptive weights receding horizon control (AWRHC) for trajectory tracking of a robot is presented. Because of the physical constraints of the robot, the conventional receding horizon control (RHC) may result in some perturbations from the reference trajectory when it is near the desired trajectory. The adaptive weights adjust the preferences for the way-points selected from the reference trajectory. The simulation results of RHC were compared with AWRHC for straight and circular trajectory tracking. The evaluation of both RHC strategies were carried out by Grey Wolf Optimizer (GWO). The AWRHC approach significantly reduces perturbations which results in quicker path following with lower path transverse at the cost of negligible increase in computation time.

Original languageEnglish
Title of host publication2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1343-1348
Number of pages6
ISBN (Electronic)9781728110899
Publication statusPublished - 23 Sept 2020
Externally publishedYes
Event59th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2020 - Chiang Mai, Thailand
Duration: 23 Sept 202026 Sept 2020

Publication series

Name2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2020

Conference

Conference59th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2020
Country/TerritoryThailand
CityChiang Mai
Period23/09/2026/09/20

Keywords

  • Adaptive Control
  • Adaptive Weights
  • Model Predictive Control
  • Path Following
  • Receding Horizon Control
  • Trajectory Tracking

ASJC Scopus subject areas

  • Control and Optimization
  • Instrumentation
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Decision Sciences (miscellaneous)
  • Industrial and Manufacturing Engineering

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