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Sliding-Mode-Disturbance-Observer-Based Robust Tracking Control for Omnidirectional Mobile Robots with Kinematic and Dynamic Uncertainties
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Publication Year
2021-04-01
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
IEEE/ASME Transactions on Mechatronics, Vol.26, pp.741-752
Keyword
Kinematic and dynamic uncertaintiesomnidirectional mobile robot (OMR)robust tracking controlsliding mode disturbance observer (SMDOB)system identification
Mesh Keyword
Disturbance observerDynamic uncertaintyKinematic uncertaintyKinematics and dynamicsOmnidirectional mobile robotRobust tracking controlSystem identification methodsTracking controller
All Science Classification Codes (ASJC)
Control and Systems EngineeringComputer Science ApplicationsElectrical and Electronic Engineering
Abstract
In this article, a robust tracking control method is developed for omnidirectional mobile robots (OMRs) with uncertainties in the kinematics and dynamics. The kinematic and dynamic uncertainties that significantly degrade the OMR tracking control performance should be simultaneously compensated, which has not been achieved by the existing OMR tracking control methods. Therefore, the OMR dynamics containing the actuator dynamics and dynamic uncertainties are obtained by including the friction present in the OMR and are identified using a system identification method for the actual OMR system. The kinematic uncertainties present in the OMR kinematics are then derived unlike the existing studies that do not consider them. A sliding mode disturbance observer is proposed to estimate these kinematic uncertainties. A robust backstepping-like feedback linearization tracking controller using estimates of both the kinematic and dynamic uncertainties is also proposed to compensate for these uncertainties. The proposed method is validated through a stability analysis and simulation and experimental results using an actually implemented OMR system.
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/31972
DOI
https://doi.org/10.1109/tmech.2020.2998506
Fulltext

Type
Article
Funding
Manuscript received January 14, 2020; revised April 9, 2020; accepted May 23, 2020. Date of publication May 29, 2020; date of current version April 15, 2021. This work was supported in part by the Korea Electric Power Corporation under Grant R19XO01-21 and in part by the National Research Foundation of Korea grant funded by the Korea government (2020R1A2C101226111). Recommended by Technical Editor J. Yu and Senior Editor M. Basin. (Corresponding author: Dongkyoung Chwa.) Sangyoon Jeong is with Hyundai Robotics, Sungnam 13615, South Korea (e-mail: fnxmaktm@ajou.ac.kr).
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Chwa, Dongkyoung Image
Chwa, Dongkyoung좌동경
Department of Electrical and Computer Engineering
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