@inproceedings{9fcc58f4f3424f1a8dce7a5cea929a27,
title = "Microcontroller-Based Intelligent Control for Reaction Wheel Pendulums Using a Fuzzy Broad-Learning System",
abstract = "This study presents an adaptive fuzzy broad-learning neural control (AFBNC) system applied to a reaction wheel pendulum without knowing its dynamic model. The AFBNC system uses a fuzzy broad-learning system (FBLS) to approximate an ideal controller online with keeping the reaction wheel pendulum balance. Moreover, the gradient descent method and chain rule are applied to online adjust all parameters of the FBLS with keeping the closed-loop control system stable. Finally, to implement the control algorithms and conduct experiments, a prototype of the reaction wheel pendulum is designed using a low-cost microcontroller. The experimental results demonstrate the effectiveness of the proposed AFBNC system using low-cost hardware.",
author = "Chen, {Bo Rui} and Hsu, {Chun Fei} and Wu, {Bing Fei}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2022 ; Conference date: 03-11-2022 Through 05-11-2022",
year = "2022",
doi = "10.1109/iFUZZY55320.2022.9985220",
language = "English",
series = "2022 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2022",
address = "United States",
}