Iterative-learning-based tracking control of a two-wheeled mobile robot with model uncertainties and unknown periodic disturbances

In this paper, we develop an adaptive iterative learning approach to investigate the trajectory tracking control issue for a class of two-wheeled mobile robots subject to model uncertainties and unknown disturbances. First, we derive the nonlinear velocity error dynamics. Then a parameterization-bas...

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Bibliographic Details
Published inJournal of the Franklin Institute Vol. 361; no. 11; p. 106962
Main Authors Yu, Lin, Xiong, Junlin, Xie, Min
Format Journal Article
LanguageEnglish
Published Elsevier Inc 01.07.2024
Subjects
Adaptive control
Model uncertainty
Robust control
Wheeled mobile robot
Robust control
Model uncertainty
Wheeled mobile robot
Adaptive control
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ISSN0016-0032
1879-2693
DOI10.1016/j.jfranklin.2024.106962

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Summary:In this paper, we develop an adaptive iterative learning approach to investigate the trajectory tracking control issue for a class of two-wheeled mobile robots subject to model uncertainties and unknown disturbances. First, we derive the nonlinear velocity error dynamics. Then a parameterization-based adaptive iterative learning control scheme is adopted to achieve precise tracking, along with logic-based update law for the estimated period and bound of the disturbance. Moreover, the boundness of all the closed-loop signals is rigorously analyzed based on the Lyapunov stability theory to provide the theoretical foundation for the proposed method. The experimental results show the efficacy and viability of our results.
ISSN:0016-0032
1879-2693
DOI:10.1016/j.jfranklin.2024.106962