@article{ref1,
title="H ∞ time-delayed fractional order adaptive sliding mode control for two-wheel self-balancing vehicles",
journal="Computational intelligence and neuroscience",
year="2020",
author="Xue, Han and Fang, Qionglin and Zhong, Jifeng and Shao, Zhe-Ping",
volume="2020",
number="",
pages="e4529131-e4529131",
abstract="In this paper, a time-delayed fractional order adaptive sliding mode control algorithm is proposed for a two-wheel self-balancing vehicle system. The closed-loop system is proved based on the Lyapunov-Razumikhin function. The switching function is designed to make the system robust when facing uncertainties and external disturbances. It is designed to avoid monotonically increasing gains and can handle state-dependent uncertainties without a prior bound. The two-wheel self-balancing vehicle used in the experiment consists of a gyroscope MPU-6050 and accelerometer, a motor driving circuit composed of a motor driving chip TB6612FNG, and STM32F103x8B that is selected as the control core. The experimental results show that the time-delayed fractional order adaptive sliding mode control algorithm can make the vehicle achieve autonomous balance and quickly restore its stable state while appropriate disturbance is introduced.<p /> <p>Language: en</p>",
language="en",
issn="1687-5265",
doi="10.1155/2020/4529131",
url="http://dx.doi.org/10.1155/2020/4529131"
}