Kalman Filter-Based Data-Driven Robust Model-Free Adaptive Predictive Control of a Complicated Industrial Process

The automatic control of blast furnace (BF) ironmaking process has always been an important yet arduous task in metallurgic engineering and automation. In this article, a novel Kalman filter-based robust model-free adaptive predictive control (MFAPC) method is proposed for the direct data-driven con...

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Vydané v:	IEEE transactions on automation science and engineering Ročník 19; číslo 2; s. 788 - 803
Hlavní autori:	Zhou, Ping, Zhang, Shuai, Wen, Liang, Fu, Jun, Chai, Tianyou, Wang, Hong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.04.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptation models Adaptive control Automatic control Blast furnace (BF) ironmaking process Blast furnace practice Control methods Control systems design Controllers Data integrity Data loss direct data-driven control Iron Ironmaking Jacobi matrix method Jacobian matrix Kalman filters Linearization Loss measurement Missing data Multilayers multiparameter sensitivity analysis Multivariable control Multivariate analysis Noise Noise measurement Prediction models Predictive control Predictive models Process control Quality control Robust control robust mechanism robust model-free adaptive predictive control (MFAPC) Stability analysis
ISSN:	1545-5955, 1558-3783
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