| A new method for stabilization of networked control systems with random delays L Zhang, Y Shi, T Chen, B Huang IEEE Transactions on automatic control 50 (8), 1177-1181, 2005 | 1078 | 2005 |
| Data mining and analytics in the process industry: the role of machine learning Z Ge, Z Song, SX Ding, B Huang IEEE Access 5, 20590-20616, 2017 | 992 | 2017 |
| Performance assessment of control loops: theory and applications B Huang, SL Shah Springer Science & Business Media, 1999 | 705* | 1999 |
| Deep learning-based feature representation and its application for soft sensor modeling with variable-wise weighted SAE X Yuan, B Huang, Y Wang, C Yang, W Gui IEEE Transactions on Industrial Informatics 14 (7), 3235-3243, 2018 | 584 | 2018 |
| A review on reinforcement learning: Introduction and applications in industrial process control R Nian, J Liu, B Huang Computers & Chemical Engineering 139, 106886, 2020 | 554 | 2020 |
| Dynamic modeling, predictive control and performance monitoring: A data-driven subspace approach B Huang, R Kadali Springer, 2008 | 446 | 2008 |
| Data-driven fault diagnosis for traction systems in high-speed trains: A survey, challenges, and perspectives H Chen, B Jiang, SX Ding, B Huang IEEE Transactions on Intelligent Transportation Systems 23 (3), 1700-1716, 2020 | 387 | 2020 |
| Performance-driven distributed PCA process monitoring based on fault-relevant variable selection and Bayesian inference Q Jiang, X Yan, B Huang IEEE Transactions on Industrial Electronics 63 (1), 377-386, 2015 | 357 | 2015 |
| Subspace method aided data-driven design of fault detection and isolation systems SX Ding, P Zhang, A Naik, EL Ding, B Huang Journal of process control 19 (9), 1496-1510, 2009 | 354 | 2009 |
| Good, bad or optimal? Performance assessment of multivariable processes B Huang, SL Shah, EK Kwok Automatica 33 (6), 1175-1183, 1997 | 354 | 1997 |
| Detection of multiple oscillations in control loops NF Thornhill, B Huang, H Zhang Journal of Process Control 13 (1), 91-100, 2003 | 346 | 2003 |
| Detection and diagnosis of stiction in control loops: state of the art and advanced methods M Jelali, B Huang Springer Science & Business Media, 2009 | 281 | 2009 |
| Design of inferential sensors in the process industry: A review of Bayesian methods S Khatibisepehr, B Huang, S Khare Journal of Process Control 23 (10), 1575-1596, 2013 | 277 | 2013 |
| Review and perspectives of data-driven distributed monitoring for industrial plant-wide processes Q Jiang, X Yan, B Huang Industrial & Engineering Chemistry Research 58 (29), 12899-12912, 2019 | 273 | 2019 |
| Hierarchical quality-relevant feature representation for soft sensor modeling: a novel deep learning strategy X Yuan, J Zhou, B Huang, Y Wang, C Yang, W Gui IEEE Transactions on Industrial Informatics 16 (6), 3721-3730, 2019 | 250 | 2019 |
| A full‐condition monitoring method for nonstationary dynamic chemical processes with cointegration and slow feature analysis C Zhao, B Huang AIChE Journal 64 (5), 1662-1681, 2018 | 237 | 2018 |
| A data driven subspace approach to predictive controller design R Kadali, B Huang, A Rossiter Control engineering practice 11 (3), 261-278, 2003 | 237 | 2003 |
| Closed-loop subspace identification: an orthogonal projection approach B Huang, SX Ding, SJ Qin Journal of process control 15 (1), 53-66, 2005 | 223 | 2005 |
| Robust reliable control for a class of uncertain nonlinear state-delayed systems Z Wang, B Huang, H Unbehauen Automatica 35 (5), 955-963, 1999 | 216 | 1999 |
| H∞ model reduction of Markovian jump linear systems L Zhang, B Huang, J Lam Systems & Control Letters 50 (2), 103-118, 2003 | 213 | 2003 |