New kernel independent and principal components analysis‐based process monitoring approach with application to hot strip mill process-Reference-Cited by-同舟云学术

New kernel independent and principal components analysis‐based process monitoring approach with application to hot strip mill process

Published:2014-11 Issue:16 Volume:8 Page:1723-1731
ISSN:1751-8652
Container-title:IET Control Theory & Applications
language:en
Short-container-title:IET Control Theory & Applications

Author:

Peng Kaixiang¹,Zhang Kai¹,He Xiao²,Li Gang²,Yang Xu¹

Affiliation:

1. Key Laboratory for Advanced Control of Iron and Steel Process, School of Automation and Electrical Engineering, University of Science and Technology BeijingBeijing100083People's Republic of China

2. Department of AutomationTNList, Tsinghua UniversityBeijing100084People's Republic of China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Beijing Municipality

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Control and Optimization,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-cta.2013.0691

Reference35 articles.

1. Fault Detection for Markovian Jump Systems With Sensor Saturations and Randomly Varying Nonlinearities

2. Kalman filter for parametric fault detection: an internal model principle-based approach

3. On Nonlinear $H_{\infty }$ Filtering for Discrete-Time Stochastic Systems With Missing Measurements

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