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Extreme-learning-machine-based robust integral terminal sliding mode control of bicycle robot
- Source :
- Chen, L., Yan, B., Wang, H. <
- Publication Year :
- 2022
-
Abstract
- In this paper, an extreme-learning-machine (ELM)-based robust integral terminal sliding mode (ITSM) control scheme is developed for a bicycle robot (BR) to achieve balancing target. First, the bicycle robot equipped with a reaction wheel is formulated by a second-order mathematical model with uncertainties. Then, an ITSM controller is designed for the balancing control of the BR, where an ELM scheme is designed as a compensator for estimating lumped uncertainties of the system. The stability proof of the closed-loop control system is presented based on Lyapunov theory. Comparative experimental results are demonstrated to verify the superior balancing performance of the proposed control.
Details
- Database :
- OAIster
- Journal :
- Chen, L., Yan, B., Wang, H. <
- Notes :
- English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1311092769
- Document Type :
- Electronic Resource