The role of ai, machine learning, and big data in digital twinning: A systematic literature review, challenges, and opportunities
Digital twinning is one of the top ten technology trends in the last couple of years, due to its
high applicability in the industrial sector. The integration of big data analytics and artificial …
high applicability in the industrial sector. The integration of big data analytics and artificial …
A survey on active fault-tolerant control systems
Faults and failures in the system components are two main reasons for the instability and the
degradation in control performance. In recent decades, fault-tolerant control (FTC) …
degradation in control performance. In recent decades, fault-tolerant control (FTC) …
A digital-twin-assisted fault diagnosis using deep transfer learning
Y Xu, Y Sun, X Liu, Y Zheng - Ieee Access, 2019 - ieeexplore.ieee.org
Digital twin is a significant way to achieve smart manufacturing, and provides a new
paradigm for fault diagnosis. Traditional data-based fault diagnosis methods mostly assume …
paradigm for fault diagnosis. Traditional data-based fault diagnosis methods mostly assume …
A survey on FinTech
As a new term in the financial industry, FinTech has become a popular term that describes
novel technologies adopted by the financial service institutions. This term covers a large …
novel technologies adopted by the financial service institutions. This term covers a large …
Robust backstepping sliding-mode control and observer-based fault estimation for a quadrotor UAV
F Chen, R Jiang, K Zhang, B Jiang… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
This study gives the mathematic model of a quadrotor unmanned aerial vehicle (UAV) and
then proposes a robust nonlinear controller which combines the sliding-mode control …
then proposes a robust nonlinear controller which combines the sliding-mode control …
Broad convolutional neural network based industrial process fault diagnosis with incremental learning capability
Fault diagnosis, which identifies the root cause of the observed out-of-control status, is
essential to counteracting or eliminating faults in industrial processes. Many conventional …
essential to counteracting or eliminating faults in industrial processes. Many conventional …
Data-driven monitoring and safety control of industrial cyber-physical systems: Basics and beyond
Industrial cyber-physical systems (ICPSs) are the backbones of Industry 4.0 and as such,
have become a core transdisciplinary area of research, both in industry and academia. New …
have become a core transdisciplinary area of research, both in industry and academia. New …
A novel multivariate statistical process monitoring algorithm: Orthonormal subspace analysis
Z Lou, Y Wang, Y Si, S Lu - Automatica, 2022 - Elsevier
Partial least squares (PLS) and canonical correlation analysis (CCA) are two most popular
key performance indicators (KPI) monitoring algorithms, which have shortcomings in dealing …
key performance indicators (KPI) monitoring algorithms, which have shortcomings in dealing …
Sequential fault diagnosis based on LSTM neural network
Fault diagnosis of chemical process data becomes one of the most important directions in
research and practice. Conventional fault diagnosis and classification methods first extract …
research and practice. Conventional fault diagnosis and classification methods first extract …
Value iteration adaptive dynamic programming for optimal control of discrete-time nonlinear systems
In this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed
to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear …
to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear …