Yuanqiang Zhou - Publications

Preprints

• Zean Li, Shengnian Yu, Jie Lei, Mingrui Wang, Wenyi Li, Yuanqiang Zhou, and Hong Chen, “Bridging tradition and intelligence: A comprehensive survey of adaptive predictive control paradigms,”
  submitted for publication, 2026.

• Yan-Ran Zhu, Yuanqiang Zhou, Dewei Li, Furong Gao, and Hong Chen, “Disturbance observer-based DMPC with event-triggered communication for nonlinear interconnected systems,”
  submitted for publication, 2026.

• Zhongxing Yang, Hongbo Zhao, Jindong Zhang, Yikang Zhang, Jiale Wang, Yuanqiang Zhou, Pan Li, Qijun Chen, and Rui Fan, “Reinforcement learning for humanoid-style stair climbing in wheeled bipedal robots,”
  submitted for publication, 2026.

• Yuanqiang Zhou, Zilong Yin, Yan-Ran Zhu, Haoyu Wang, Dewei Li, Furong Gao, and Hong Chen, “FedRMPC: Federated robust model predictive control via uncertainty and proximal regularizations,”
  submitted for publication, 2026.

• Rui Chen, Husnain Ali, Shu Liang, Yuanqiang Zhou, Furong Gao, and Hong Chen, “An integrated multiscale Granger causality algorithm for root cause diagnosis of non-stationary processes,”
  submitted for publication, 2026.

• Yuanqiang Zhou, Yan-Ran Zhu, Zilong Yin, Dewei Li, Furong Gao, and Hong Chen, “Dynamic event-triggered distributed predictive control with adaptive thresholding for continuous-time interconnected systems,”
  submitted for publication, 2025.

• Yuanqiang Zhou, Dewei Li, and Yugeng Xi, “Data-driven predictive control for continuous-time industrial processes with completely unknown dynamics,”
  arXiv preprint arXiv:2012.03452, 2020.

• Yuanqiang Zhou, Dewei Li, Yugeng Xi, and Yuwen Xu, “Data-driven approximation for feasible regions in nonlinear model predictive control,”
  arXiv preprint arXiv:2012.03428, 2020.

Survey and Review Papers

• Yuanqiang Zhou and Furong Gao, “Smart batch process: The evolution from 1D and 2D to new 3D perspectives in the era of Big Data,”
  Journal of Process Control, vol. 130, pp. 103088, 2023. (SCI & EI; JCR Q1, IF = 4.2)

• Yuanqiang Zhou, Zhixing Cao, Jingyi Lu, Chunhui Zhao, Dewei Li, and Furong Gao, “Objectives, challenges, and prospects of batch processes: Arising from injection molding applications,”
  Korean Journal of Chemical Engineering, vol. 39, no. 12, pp. 3179-3189, 2022. (SCI & EI; JCR Q1, IF = 3.146)

• Xin Lai, Quanwei Chen, Xiaopeng Tang, Yuanqiang Zhou, Furong Gao, Yue Guo, Rohit Bhagat, and Yuejiu Zheng, “Critical review of life cycle assessment of lithium-ion batteries for electric vehicles: A lifespan perspective,”
  eTransportation, vol. 12, pp. 100169, 2022. (SCI & EI; JCR Q1, IF = 13.661)

• Rui Chen, Yuanqiang Zhou, Jianguo Wang, Yuan Yao, Xiangyun Ye, Jialin Kang, “Root cause diagnosis in industrial processes via multi-time scale Granger causality analysis,”
  Journal of the Taiwan Institute of Chemical Engineers, pp. 106780, doi: 10.1016/j.jtice.2026.106780, 2026.(SCI & EI; JCR Q1, IF = 6.3)

• Husnain Ali, Debrina Andriani, Rizwan Safdar, Teh Sabariah Abd Manan, Guangze Hu, Yuanqiang Zhou, Xiangrui Zhang, Yuan Yao, Zhixing Cao, Jinfeng Liu, and Furong Gao, “A hybrid DiGLPP–Kolmogorov–Arnold network framework for robust fault detection in industrial chemical processes,”
  Process Safety and Environmental Protection, pp. 108854, doi: 10.1016/j.psep.2026.108854, 2026.(SCI & EI; JCR Q1, IF = 7.8)

• Xiaofei Han, Kang Li, Furong Gao, Yuanqiang Zhou, “Historical data-driven self-learning control of battery charging with convex mapping constraints,”
  Journal of Energy Storage, vol. 152, pp. 120430, doi: 10.1016/j.est.2026.120430, 2026.(SCI & EI; JCR Q1, IF = 9.8)

• Yuanqiang Zhou, Mingrui Wang, Yuhang He, Jia Xu, Dewei Li, and Hong Chen, “The Effective Singular Value Ratio: A novel criterion for adaptive data selection in DeePC,”
  IEEE Control Systems Letters, vol. 9, pp. 2475-2680, doi: 10.1109/LCSYS.2025.3638971, 2025.(SCI & EI; JCR Q2, IF = 2)

• Wentao Xu, Zilong Yin, Yuanqiang Zhou, Yanran Zhu, Mingrui Wang, Jie Lei, and Hong Chen, “ChatMPC: A language-driven model predictive control framework for adaptive and personalized autonomous driving,”
  Autonomous Intelligent Systems, vol. 5, pp. 27, doi: 10.1007/s43684-025-00116-x, 2025. (EI)

• Siyuan Tang, Zheren Zhu, Yuanqiang Zhou, Bingbing Shen, Ziyuan Shen, Zeyu Yang, Le Yao, “Variable structure learning-based spatio-temporal graph convolutional networks for chemical process quality prediction with SHAP-enhanced interpretability,”
  Processes, vol. 13, no. 11, pp. 3751, doi: 10.3390/pr13113751, 2025. (SCI & EI; JCR Q3, IF = 2.8)

• Rui Chen, Husnain Ali, Shu Liang, Yuanqiang Zhou, and Furong Gao, “A correction symbol Granger causality approach to root cause diagnosis of non-stationary industrial processes,”
  Computers & Chemical Engineering, vol. 205, pp. 109479, doi: 10.1016/j.compchemeng.2025.109479, 2026. (SCI & EI; JCR Q1, IF = 3.9)

• Husnain Ali, Rizwan Safdar, Weilong Ding, Yuanqiang Zhou, Yuan Yao, Le Yao, and Furong Gao, “Intelligent machine learning-based multi-model fusion monitoring: application to industrial physio-chemical systems,”
  Control Engineering Practice, vol. 162, pp. 106361, doi: 10.1016/j.conengprac.2025.106361, 2025. (SCI & EI; JCR Q1, IF = 5.4)

  (This paper is recognized as one of the ESI Highly Cited Papers)

• Kaihua Gao, Jingyi Lu, Yuanqiang Zhou, and Furong Gao, “A computationally efficient policy optimization scheme in feedback iterative learning control for nonlinear batch process,”
  Computers & Chemical Engineering, vol. 195, pp. 109005, doi: 10.1016/j.compchemeng.2025.109005, 2025. (SCI & EI; JCR Q1, IF = 3.9)

• Husnain Ali, Rizwan Safdar, Yuanqiang Zhou, Yuan Yao, Le Yao, Zheng Zhang, Weilong Ding, and Furong Gao, “A novel dynamic machine learning-based explainable fusion monitoring: Application to industrial and chemical processes,”
  Machine Learning: Science and Technology, vol. 6, no. 1, pp. 015005, doi: 10.1088/2632-2153/ada088, 2025. (SCI & EI; JCR Q1, IF = 6.3)

  (This paper is recognized as one of the ESI Highly Cited Papers)

• Kaihua Gao, Yuanqiang Zhou, Furong Gao, and Jingyi Lu, “Optimally selected cycle based ILC for system with randomly varying initial state,”
  IEEE Transactions on Automatic Control, vol. 70, no. 4, pp. 2714-2721, doi: 10.1109/TAC.2024.3494393, 2025. (SCI & EI; JCR Q1, IF = 6.2)

• Yuanqiang Zhou, Huanjia Hu, Weilong Ding, Kaihua Gao, Dewei Li, and Furong Gao, “Cooperative distributed predictive control for smart injection molding systems with one-tap memory,”
  IEEE Transactions on Industrial Informatics, vol. 20, no. 6, pp. 8850-8860, doi: 10.1109/TII.2024.3378838, 2024. [Data]. (SCI & EI; JCR Q1, IF = 12.3)

• Husnain Ali, Rizwan Safdar, Muhammad Hammad Rasool, Hirra Anjum, Yuanqiang Zhou, Yuan Yao, Le Yao, and Furong Gao, “Advance industrial monitoring of physio-chemical processes using novel integrated machine learning approach,”
  Journal of Industrial Information Integration, vol. 42, pp. 100709, doi: 10.1016/j.jii.2024.100709, 2024. (SCI & EI; JCR Q1, IF = 10.4)

• Yuanqiang Zhou, Xiaopeng Tang, Dewei Li, Xin Lai, and Furong Gao, “Combined iterative learning and model predictive control scheme for nonlinear systems,”
  IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 54, no. 6, pp. 3558-3567, doi: 10.1109/TSMC.2024.3368108, 2024. [Code & Data]. (SCI & EI; JCR Q1, IF = 8.7)

• Husnain Ali, Rizwan Safdar, Yuanqiang Zhou, Yuan Yao, Le Yao, Zheng Zhang, Muhammad Hammad Rasool, and Furong Gao, “Robust statistical industrial fault monitoring: A machine learning-based distributed CCA and low frequency control charts,”
  Chemical Engineering Science, vol. 299, pp. 120460, doi: 10.1016/j.ces.2024.120460, 2024. (SCI & EI; JCR Q1, IF = 4.1)

• Weiguo Ma, Yuanqiang Zhou, Xin Lai, and Furong Gao, “Event-triggered H-infinity filtering for a class of nonlinear systems under DoS attacks,”
  Circuits, Systems, and Signal Processing, doi: 10.1007/s00034-024-02775-2, 2024. [Code & Data]. (SCI & EI; JCR Q3, IF = 2.311)

• Kaihua Gao, Yuanqiang Zhou, Jingyi Lu, and Furong Gao, “A selective migration-based improved GPR modeling method for batch process,”
  IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 54, no. 5, pp. 3097-3109, doi: 10.1109/TSMC.2024.3353802, 2024. (SCI & EI; JCR Q1, IF = 8.7)

• Yuanqiang Zhou and Furong Gao, “Smart batch process: The evolution from 1D and 2D to new 3D perspectives in the era of Big Data,”
  Journal of Process Control, vol. 130, pp. 103088, doi: 10.1016/j.jprocont.2023.103088, 2023. (SCI & EI; JCR Q1, IF = 4.2)

• Xiaopeng Tang, Xin Lai, Changfu Zou, Yuanqiang Zhou, Jiajun Zhu, Yuejiu Zheng, and Furong Gao, “Detecting abnormality of battery lifetime from first-cycle data using few-shot learning,”
  Advanced Science, vol. 11, no. 6, pp. 2305315, doi: 10.1002/advs.202305315, 2023. [Code & Data]. (SCI & EI; JCR Q1, IF = 17.521)

• Xin Lai, Ming Yuan, Xiaopeng Tang, Yuejiu Zheng, Jiajun Zhu, Yuedong Sun, Yuanqiang Zhou, and Furong Gao, “State-of-power estimation for Lithium-Ion batteries based on a frequency-dependent integer-order model,”
  Journal of Power Sources, vol. 594, pp. 234000, doi:10.1016/j.jpowsour.2023.234000; 2023. (SCI & EI; JCR Q1, IF = 9.2)

• Yuanqiang Zhou, Kaihua Gao, Xiaopeng Tang, Huanjia Hu, Dewei Li, and Furong Gao, “Conic input mapping design of constrained optimal iterative learning controller for uncertain systems,”
  IEEE Transactions on Cybernetics, vol. 53, no. 3, pp. 1843-1855, doi: 10.1109/TCYB.2022.3155754, 2023. (SCI & EI; JCR Q1, IF = 19.118)

• Xiaopeng Tang, Jiajun Zhu, Xin Lai, Yuanqiang Zhou, Yuejiu Zheng, and Furong Gao, “An aging- and load-insensitive method for quantitatively detecting the battery internal-short-circuit resistance,”
  Chemical Engineering Journal, vol. 476, pp. 146467, doi: 10.1016/j.cej.2023.146467, 2023. (SCI & EI; JCR Q1, IF = 15.1)

• Xin Lai, Yi Yao, Xiaopeng Tang, Yuejiu Zheng, Yuanqiang Zhou, Yuedong Sun, and Furong Gao, “Voltage profile reconstruction and state of health estimation for lithium-ion batteries under dynamic working conditions,”
  Energy, vol. 282, pp. 128971, doi: 10.1016/j.energy.2023.128971, 2023. (SCI & EI; JCR Q1, IF = 9)

• Yuanqiang Zhou, Dewei Li, and Furong Gao, “Input mapping design for batch-to-batch optimization with limited memory,”
  IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 70, no. 1, pp. 171-175, doi: 10.1109/TCSII.2022.3205925, 2023. (SCI & EI; JCR Q1, IF = 3.691)

• Xiaopeng Tang, Xin Lai, Qi Liu, Yuejiu Zheng, Yuanqiang Zhou, Yunjie Ma, and Furong Gao, “Predicting battery impedance spectra from 10-second pulse tests under 10Hz sampling rate,”
  iScience, vol. 26, no. 6, pp. 106821, doi: 10.1016/j.isci.2023.106821, 2023. [Code & Data]. (SCI & EI; JCR Q1, IF = 6.107)

• Xin Lai, Bin Li, Xiaopeng Tang, Yuanqiang Zhou, Yuejiu Zheng, and Furong Gao, “A quantitative method for early-stage detection of the internal-short-circuit in Lithium-ion battery pack under float-charging conditions,”
  Journal of Power Sources, vol. 573, pp. 233109, doi: 10.1016/j.jpowsour.2023.233109, 2023. (SCI & EI; JCR Q1, IF = 9.794)

• Yuanqiang Zhou, Dewei Li, and Furong Gao, “Data-driven optimal synchronization control for leader-follower multi-agent systems,”
  IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 53, no. 1, pp. 495-503, doi: 10.1109/TSMC.2022.3184001, 2023. (SCI & EI; JCR Q1, IF = 13.451)

• Xiaopeng Tang, Yuanqiang Zhou, Furong Gao, and Xin Lai, “Joint estimation of state-of-charge and state-of-health for all cells in the battery pack using “leader-follower” strategy,”
  eTransportation, vol. 15, pp. 100213, doi: 10.1016/j.etran.2022.100213, 2022. (SCI & EI; JCR Q1, IF = 13.661)
  (This paper wins the Best Annual Research Paper award of the Elsevier Journal, eTransportation)

• Xin Lai, Huanghui Gu, Quanwei Chen, Xiaopeng Tang, Yuanqiang Zhou, Furong Gao, Xuebing Han, Yue Guo, Rohit Bhagat, and Yuejiu Zheng, “Investigating greenhouse gas emissions and environmental impacts from the production of lithium-ion batteries in China,”
  Journal of Cleaner Production, vol. 372, pp. 133756, doi: 10.1016/j.jclepro.2022.133756, 2022. (SCI & EI; JCR Q1, IF = 11.072)

• Xin Lai, Quanwei Chen, Xiaopeng Tang, Yuanqiang Zhou, Furong Gao, Yue Guo, Rohit Bhagat, and Yuejiu Zheng, “Critical review of life cycle assessment of lithium-ion batteries for electric vehicles: A lifespan perspective,”
  eTransportation, vol. 12, pp. 100169, doi: 10.1016/j.etran.2022.100169, 2022. (SCI & EI; JCR Q1, IF = 13.661)
  (This paper wins the Best Annual Review Paper award of the Elsevier Journal, eTransportation, and is recognized as one of the ESI Highly Cited Papers)

• Yuanqiang Zhou, Zhixing Cao, Jingyi Lu, Chunhui Zhao, Dewei Li, and Furong Gao, “Objectives, challenges, and prospects of batch processes: Arising from injection molding applications,”
  Korean Journal of Chemical Engineering, vol. 39, no. 12, pp. 3179-3189, doi: 10.1007/s11814-022-1294-x, 2022. (SCI & EI; JCR Q1, IF = 3.146)

• Yuanqiang Zhou, Dewei Li, Yugeng Xi, and Furong Gao, “Event-triggered distributed robust model predictive control for a class of nonlinear interconnected systems,”
  Automatica, vol. 136, pp. 110039, doi: 10.1016/j.automatica.2021.110039, 2022. [Code]. (SCI & EI; JCR Q1, IF = 6.150)

• Yuanqiang Zhou, Dewei Li, and Furong Gao, “Conic iterative learning control using distinct data for constrained batch processes with state-dependent uncertainty,”
  IEEE Transactions on Industrial Informatics, vol. 18, no. 5, pp. 3095-3104, doi: 10.1109/TII.2021.3107522, 2022. (SCI & EI; JCR Q1, IF = 11.648)

• Yuanqiang Zhou, Kyriakos G. Vamvoudakis, Wassim M. Haddad, and Zhong-Ping Jiang, “A secure control learning framework for cyber-physical systems under sensor and actuator attacks,”
  IEEE Transactions on Cybernetics, vol. 51, no. 9, pp. 4648-4660, doi: 10.1109/TCYB.2020.3006871, 2021. (SCI & EI; JCR Q1, IF = 11.448)

• Yuanqiang Zhou, Kaihua Gao, Dewei Li, Zuhua Xu, and Furong Gao, “Data-efficient constrained learning for optimal tracking of batch processes,”
  Industrial & Engineering Chemistry Research, vol. 60, no. 43, pp. 15658-15668, doi: 10.1021/acs.iecr.1c02706, 2021. [Code & Data]. (SCI & EI; JCR Q1, IF = 4.326)

• Yuanqiang Zhou, Dewei Li, and Furong Gao, “Optimal synchronization control for heterogeneous multi-agent systems: Online adaptive learning solutions,”
  Asian Journal of Control, vol. 24, no. 5, pp. 2352-2362, doi: 10.1002/asjc.2642, 2021. (SCI & EI; JCR Q2, IF = 3.452)

• Yuanqiang Zhou, Dewei Li, Yugeng Xi, and Zhongxue Gan, “Synthesis of model predictive control based on data-driven learning,”
  Science China: Information Sciences, vol. 63, no. 8, pp. 189204, doi: 10.1007/s11432-018-9645-3, 2020. (SCI & EI; JCR Q1, IF = 3.304)

• Yuanqiang Zhou, Dewei Li, Yugeng Xi, and Zhongxue Gan, “Periodic event-triggered control for distributed networked multi-agents with asynchronous communication: A predictive control approach,”
  International Journal of Robust and Nonlinear Control, vol. 29, no. 1, pp. 43-46, doi: 10.1002/rnc.4387, 2019. (SCI & EI; JCR Q1, IF = 4.406)
  (This paper is listed in the Top Downloaded Papers of 2018-2019, International Journal of Robust and Nonlinear Control)

• Yuanqiang Zhou, Dewei Li, Jianbo Lu, Yugeng Xi, and Lihui Cen, “Networked and distributed predictive control of non-linear systems subject to asynchronous communication,”
  IET Control Theory and Applications, vol. 12, no. 4, pp. 504-514, doi: 10.1049/iet-cta.2017.0674, 2018. (SCI & EI; JCR Q1, IF = 3.343)

• Yonghe Zhang, Xuwen Liang, Yuanqiang Zhou, Yanning Guo, and Guangfu Ma, “Full-Matrix MIMO QFT controller design for drag-free satellites in dual formation,”
  Journal of Astronautics, vol. 37, no.7, pp. 819-828, 2016. (EI)