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Adaptive integral terminal sliding mode control of unmanned bicycle via ELM and barrier function

Published online by Cambridge University Press:  12 September 2024

Long Chen ,
Zhihui Jin ,
Ke Shao ,
Guangyi Wang ,
Shuping He ,
Vladimir Stojanovic Open the ORCID record for Vladimir Stojanovic [Opens in a new window] ,
Parisa Arabzadeh Bahri  and
Hai Wang Open the ORCID record for Hai Wang [Opens in a new window]
Long Chen
Affiliation:
School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China
Zhihui Jin
Affiliation:
School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China
Ke Shao*
Affiliation:
School of Civil Aviation, Northwestern Polytechnical University, Xi’an, China
Guangyi Wang
Affiliation:
School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China
Shuping He
Affiliation:
School of Electrical Engineering and Automation, Anhui University, Hefei, China
Vladimir Stojanovic
Affiliation:
Department of Automatic Control, Robotics and Fluid Technique, University of Kragujevac, Kragujevac, Serbia
Parisa Arabzadeh Bahri
Affiliation:
School of Engineering and Energy; Centre of Water, Energy & Waste, Murdoch University, Perth, Australia
Hai Wang*
Affiliation:
School of Engineering and Energy; Centre of Water, Energy & Waste, Murdoch University, Perth, Australia
*
Corresponding authors: Hai Wang; Email: [email protected]; Ke Shao; Email: [email protected]
Corresponding authors: Hai Wang; Email: [email protected]; Ke Shao; Email: [email protected]
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Abstract

In this paper, an unmanned bicycle (UB) with a reaction wheel is designed, and a second-order mathematical model with uncertainty is established. In order to achieve excellent balancing performance of the UB system, an adaptive controller is designed, which is composed of nominal feedback control, compensating control using extreme learning machine observer and reaching control via integral terminal sliding mode (ITSM) and barrier function (BF)-based adaptive law. Owing to the features of BF-based ITSM (BFITSM), not only any uncertainty or disturbance upper bound is not needed any longer but also the finite-time convergence of the closed-loop system can be ensured with a predefined error bound. Moreover, the BF-based control gain can be adaptively adjusted according to the update of the lumped uncertainty such that the overestimation is removed. The stability analysis of the closed-loop system is given according to Lyapunov theory. Comparable experimental results on an actual UB are carried out to validate the superior balancing performance of the proposed controller.

Keywords

integral terminal sliding mode (ITSM)balancing barrier function (BF)unmanned bicycle (UB)extreme learning machine (ELM)
Type
Research Article
Information
Robotica , First View , pp. 1 - 23
Copyright
© The Author(s), 2024. Published by Cambridge University Press

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