no code implementations • 9 Jan 2022 • Bolin Li, Lijun Zhu
This paper presents an active disturbance rejection control (ADRC) scheme with an improved fractional-order extended state observer (IFO-ESO). Based on the new ADRC scheme, the open-loop transfer function of a high-order system can be approximately rendered to a so-called Weighed Bode's ideal transfer function, whose closed-loop performance is less prone to the controller parameter variations.
no code implementations • 10 Dec 2021 • Bolin Li, Lijun Zhu
This paper presents an improved active disturbance rejection control scheme (IFO-ADRC) with an improved fractional-order extended state observer (IFO-ESO).
no code implementations • 6 Dec 2021 • Bolin Li, Lijun Zhu
The frequency-domain analysis shows that the IFADRC has a stronger disturbance estimation performance for the fraction-order system than an integer-order active disturbance rejection controller (IADRC).
no code implementations • 1 Oct 2020 • Arthur J. Redfern, Lijun Zhu, Molly K. Newquist
This paper describes a CNN where all CNN style 2D convolution operations that lower to matrix matrix multiplication are fully binary.
no code implementations • 18 Jan 2019 • Lijun Zhu, Zhigang Peng, James McClellan, Chenyu Li, Dongdong Yao, Zefeng Li, Lihua Fang
In this paper, we present a CNN-based Phase- Identification Classifier (CPIC) designed for phase detection and picking on small to medium sized training datasets.
no code implementations • 14 Jun 2018 • Lijun Zhu, Zhiyong Chen, David J. Hill, Shengli Du
Specifically, the closed-loop system is associated with a pair of auxiliary input and output.
Systems and Control
1 code implementation • 7 Feb 2017 • Lijun Zhu, Lindsay Chuang, James H. McClellan, Entao Liu, Zhigang Peng
In the presence of background noise, arrival times picked from a surface microseismic data set usually include a number of false picks that can lead to uncertainty in location estimation.
no code implementations • 6 Dec 2016 • Entao Liu, Lijun Zhu, Anupama Govinda Raj, James H. McClellan, Abdullatif Al-Shuhail, SanLinn I. Kaka, Naveed Iqbal
Passive microseismic data are commonly buried in noise, which presents a significant challenge for signal detection and recovery.