Zhou Jinglin头像

Zhou Jinglin

Professor

Research direction:

100029

Education:

10 Access

  • Email: jinglinzhou@mail.buct.edu.cn
  • Office : Room 412, Science and Technology Building

Introduction

Dr. Jinglin Zhou received the BEng, MSc and Ph.D. degrees from Daqing Petroleum Institute, Hunan University, and the Institute of Automation, Chinese Academy of Sciences, in 1999, 2002 and 2005, respectively. He was an Academic Visitor at Department of Automatic Control and Systems Engineering, the University of Sheffield. Dr. Zhou is currently a professor in the College of Information Science and Technology, Beijing University of Chemical Technology. His research interests include stochastic distribution control, fault detection and diagnosis, variable structure control and their applications.


Education

Work Experience

Social Position

Social Activities

Research

Stochastic distribution control

Control-loop performance assessment

Fault detection and diagnosis

Data drive control and its application


Teaching

Modern control theory

Optimal control

Industrial data analysis technology and application


Postgraduates

Funding

  1.  01/2021~12/2024: National Science Foundation of China (Grant No. 62073023) Performance assessment of non-Gausssian feedback control loops

  2. 01/2014~12/2018: National Science Foundation of China (Grant No. 61473025). Control-loop performance assessment for output stochastic distribution control system

  3. 01/2015~12/2019: National Science Foundation of China, (Grant No. 61573052) Data-driven enhanced learning control for complex dynamic systems

  4. 01/2015~12/2019: National Science Foundation of China (Grant No. 61573050), Fault diagnosis and control under unified framework for batch process


Vertical Project

Horizontal Project

Publications

[1]     Meng Y., J Zhou J. L., Lei F. R., Li D. Z., A novel class of non-Gaussian system performance assessment and controller parameter tuning methods,ISA Transactions,2024.154, 199-212.

[2]     Zhou J. L. Yang Z. Y., Non-Gaussian quality relevant process Monitoring based on higher-order statistics projection to the latent structure and independent signal correction. Industrial & Engineering Chemistry Research. 2023 62 (6), 2777-2791.

[3]     Liu D.Zhou J.Jiang H. Adversarial autoencoder concurrent projection to latent structure and its application. Can. J. Chem. Eng. 2024, 102(1), 274. 

[4]     Wang J., Zhou J. L. and Chen X., Data-Driven Fault Detection and Reasoning for Industrial Monitoring. Springer, Singapore, 2022.

[5]     Zhou J. L., Zhang S. L. and Wang J., A dual robustness projection to latent structure method and its application, IEEE Trans. on Industrial Electronics, 2021, 68: 1604-1614.

[6]     Zhou J. L. and Yue H., Soft-bound interval control system and its robust fault-tolerant controller design, IEEE Trans. on Systems Man Cybernetics-Systems, 2021,51:378-390.

[7]     Huang Z. D. and Zhou J. L., Text removal network based on comprehensive loss evaluation and its application, Neurocomputing, 2021,466:148161

[8]     Zhou J. L., Ren Y. W. and Wang J., Quality-relevant fault monitoring based on locally linear embedding orthogonal projection to latent structure, Industrial & Engineering Chemistry Research, 2019, 58:1262–1272.

[9]     Zhou, J. L., Zhang S. L., Zhang, H. and. Wang, J.*, A Quality-Related Statistical Process Monitoring Method Based on Global plus Local Projection to Latent Structures. Ind. Eng. Chem. Res.,57: 5323–5337, 2018.

[10]   Zhang, Qichun; Zhou, Jinglin; Wang, Hong; Chai, Tianyou, Output feedback stabilization for a class of multi-variable bilinear stochastic systems with stochastic coupling attenuation, IEEE Transactions on Automatic Control, 62(6), pp 2936-2942, 2017


Awards

N/A


Patent

Honor Reward

Admissions Information