Zhenlei Wang, Professor and Doctoral Supervisor. He is a leading talent in S&T innovation under the National 10,000 Talents Program.

Prof. Wang has devoted decades to developing fundamental theories and key technologies of machine learning, intelligent control and integrated optimization for efficiently utilizing resource and energy of chemical processes.

He has been responsible for a number of national key projects and scientific research projects at the provincial and ministerial level, including one subject of the  National Science and Technology Support Program, one subject of the 863 key R&D program and one subject of the Ministry of Science and Technology's key R&D program. Responsible for the development and application of advanced control and operation optimization technology for the whole process of large-scale ethylene plants, and solved the problems of variable working points, nonlinearity, online measurement of disturbance variables and controlled variables, and multi-controller coordination of key units in the ethylene production process. The technology won the first prize of Science and Technology Progress Award of China Petroleum and Chemical Industry Federation, and has been applied in 12 large-scale ethylene production enterprises in my country. economic benefits. He has won 2 second prizes of the National Science and Technology Progress Award and 4 first prizes of the provincial and ministerial science and technology progress awards.

Moreover, Prof. Wang owns 12 patents, registered 20 computer software copyrights, authored more than 100 SCI/EI indexed articles. 

Department: Department of Automation, School of Information Science and Engineering

Address: 130 Meilong Road, Shanghai

Work Phone: 021-64253653

E-mail: wangzhen_l@ecust.edu.cn

Research Interests:

Intelligent modeling, machine learning, fault detection and diagnosis, advanced control and system integration optimization

Teaching:

Modern Control Theory, undergraduate course

Machine learning course design, undergraduate course

Adaptive Control Theory and Application, graduate course

Research Program:

• Jun. 2018 to May 2022, National Key Research and Development Program, 2018YFB1701103, Intelligent Linkage Method of Workshop Real-time Control and Device Operation Optimization, Subject leader.

• Jan. 2016 to Dec. 2020, Key Project of NSFC (National Natural Science Foundation of China) Program, 61533003, Energy Efficiency Evaluation and System Optimization Theory and Key Technologies Based on the Fusion of Complex Petrochemical Process Data and Domain Knowledge, Subject leader.

Publications:

• Wang Xiaoyang, Wang Xin, Wang Zhenlei*, Qian Feng, A novel method for detecting processes with multistate modes, Control Engineering Practice, 21 (2013), pp. 1788-1794.

• Miao Huang, Xin Wang, Zhenlei Wang*. Multiple model adaptive control for a class of linear-bounded nonlinear systems, IEEE Transactions on Automatic Control. 2015, 60(1): 271-276.

• Miao Huang, Xin Wang, Zhenlei Wang*. Multiple model self-tuning control for a class of nonlinear systems, International Journal of Control, 2015, 88(10):1-22.

• Gao Y, Wang X, Wang Z*. Fault detection for a class of industrial processes based on recursive multiple models [J]. Neurocomputing, 2015, 169:430–438.

• Kunjie Yu, Xin Wang, Zhenlei Wang*. Self-adaptive multi-objective teaching-learning-based optimization and its application in ethylene cracking furnace operation optimization. Chemometrics and Intelligent Laboratory Systems, 2015, 146: 198-210.

• Kunjie Yu, Xin Wang, Zhenlei Wang*. Multiple learning particle swarm optimization with space transformation perturbation and its application in ethylene cracking furnace optimization，Knowledge-Based Systems，2016， 96(15):  156–170

• Yu K, Wang X, Wang Z*. Constrained optimization based on improved teaching-learning-based optimization algorithm[J]. Information Sciences, 2016, 352(C):61-78.

• Yu Kunjie, Chen Xu, Wang Xin, Wang Zhenlei*. Parameters identification of photovoltaic models using self-adaptive teaching-learning-based optimization[J]. Energy Conversion and Management, 2017,145: 233-246.

• Mei H, Cheng H, Wang Z, et al.. Molecular characterization of petroleum fractions using state space representation and its application for predicting naphtha pyrolysis product distributions[J]. Chemical Engineering Science, 2017, 164: 81-89.

• Kunjie Yu, L While, M Reynolds, X Wang, JJ Liang, L Zhao, Z Wang*. Multiobjective optimization of ethylene cracking furnace system using self-adaptive multiobjective teaching-learning-based optimization. Energy[J], 2018(148): 469-481.

• Guixin Zhang, Zhenlei Wang*, Hua Mei. Sensitivity clustering and ROC curve based alarm threshold optimization[J]. Process Safety and Environmental Protection,2020,141:83-94.