Han Honggui

                       

Personal profile

Name: Han Honggui

Gender: Male

Degree: Ph.D.

Title: Professor

E-mail:rechardhan@bjut.edu.cn

Current Professional Societies:

1. Director ofEngineering Research Center of Digital Community,Ministry of Education;

2. IEEE senior member;

3. Associate-Editor for IEEE Transactions on Cybernetics;

4. Associate-Editor for International Journal of Fuzzy System;

5.Associate-Editor for Science China: Technological Sciences

Research Areas:

1. Intelligent Control Theory and Engineering

2. Artificial Intelligence

3. Civil and Environmental Engineering

Honors

1. 1st Prize of Natural Science Award from Ministry of Education, China, 2012

2. Excellent Doctoral Dissertation of Beijing Municipal Education Commison, 2012

3. Beijing Nova, 2013

4. The National Excellent Doctoral Dissertation Award Nomination, 2014

5. Hong Kong Scholar, 2014

6. 2nd Prize of the Eighth “Capital Challenge Cup” Award, 2015

7. Young Elite Scientists Sponsorship Program BY CAST, 2015

8. 1st Prize of Chinese Industry University Research Cooperation Award, 2016

9. 1st Prize of Chinese Artificial Intelligence Science and Technology ProgressAward, 2016

10. Outstanding Young Foundation BY National Natural Science of China, 2016

11. 1st Prize of the Ninth “Capital Challenge Cup, 2017

12.2nd Prize of National Science and Technology Progress Award, 2018

13.Chief Scientist of National Key Research and Development Project, 2018

14. CAA Innovation Team Award, 2019

15. Beijing Outstanding Young Scientist, 2019

Publications

I.SelectedJournal Publications

[01] Han Honggui, Liu Zheng, Hou Ying, Qiao Junfei. Data-driven Multiobjective Predictive Control for Wastewater Treatment Process,IEEE Transactions on Industrial Informatics, 2020, 16(4): 2767-2775.

[02] Han Honggui, Wu Xiaolong, Liu Hongxu, Qiao Junfei. An Efficient Optimization Method for Improving Generalization Performance of Fuzzy Neural Networks,IEEE Transactions on Fuzzy Systems, 2019, 27(7): 1347-1361.

[03] Han Honggui, Wu Xiaolong, Qiao Junfei. A Self-organizing Sliding-mode Controller for Wastewater Treatment Process,IEEE Transactions on Control Systems Technology, 2019, 27(4): 1480-1491.

[04] Han Honggui, Zhang Lu, Wu Xiaolong, Qiao Junfei.An Efficient Second-order Method for Self-organizing Fuzzy Neural Networks,IEEE Transactions on Cybernetics, 2019, 49(1): 14-26.

[05] Han Honggui, Wu Xiaolong, Zhang Lu, Qiao Junfei.Self-organizing RBF Neural Network Using an Adaptive Gradient Multiobjective Particle Swarm Optimization,IEEE Transactions on Cybernetics, 2019, 49(1): 69-82.

[06] Han Honggui, Lu Wei, Zhang Lu, Qiao Junfei. Adaptive Gradient Multiobjective Particle Swarm Optimization,IEEE Transactions on Cybernetics, 2018, 48(11): 3067-3079.

[07]Han Honggui, Wu Xiaolong, Liu Zheng, Qiao Junfei. Design of Self-organizing Intelligent Controller Using Fuzzy Neural Network,IEEE Transactions on Fuzzy Systems, 2018, 26(5): 3097-3111.

[08]Han Honggui, Lu Wei, Hou Ying, Qiao Junfei. An Adaptive-PSO-based Self-organizing RBF Neural Network,IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(1): 104-117.

[09]Han Honggui, Lu Wei, Qiao Junfei. An Adaptive Multiobjective Particle Swarm Optimization Based on Multiple Adaptive Methods,IEEE Transactions on Cybernetics, 2017, 47(9): 2754-2767.

[10]Han Honggui, Zhang Lu, Hou Ying, Qiao Junfei. Nonlinear Model Predictive Control Based on a Self-organizing Recurrent Neural Network,IEEE Transactions on Neural Networks and Learning Systems, 2016. 27(2): 402-415.

[11]Han Honggui, Zhou Wengdong, Qiao Junfei, Feng Gang. A Direct Self-constructing Neural Controller Design for a Class of Nonlinear Systems,IEEE Transactions on Neural Networks and Learning Systems, 2015. 26(6): 1312-1322.

[12]Han Honggui, Qiao Junfei. Nonlinear Model-predictive Control for Industrial Processes: An Application to Wastewater Treatment Process,IEEE Transactions on Industrial Electronics, 2014. 61(4): 1970-1982.

[13]Han Honggui, Wu Xiaolong, Qiao Junfei. Nonlinear Systems Modeling Based on Self-organizing Fuzzy-neural-network with Adaptive Computation Algorithm,IEEE Transactions on Cybernetics, 2014. 44(4): 554-564.

[14]Han Honggui, Wu Xiaolong, Qiao Junfei. Real-time Model Predictive Control Using a Self-organizing Neural Network,IEEE Transactions on Neural Networks and Learning Systems, 2013. 24(9): 1425-1436.

[15] Han Honggui, Qiao Junfei. Hierarchical-neural-network Modeling Approach to Predict Sludge Volume Index of Wastewater Treatment Process,IEEE Transactions on Control Systems Technology, 2013. 21(6): 2423-2431.

[16]Han Honggui, Qiao Junfei. Adaptive Computation Algorithm for RBF Neural Network,IEEE Transactions on Neural Networks and Learning Systems, 2012, 23(2): 342-347.

[17] Han Honggui, Zhang Huijuan, Liu Zheng, Qiao Junfei. Data-driven Decision-making Method for Membrane Fouling,Control Engineering Practice, 2020, 96(1): 104305.

[18] Han Honggui, Liu Zheng, Guo Yanan, Qiao Junfei. An Intelligent Detection Method for Bulking Sludge of Wastewater Treatment Process,Journal of Process Control, 2018, 68(1): 118-128.

[19] Han Honggui, Qiao Junfei. Nonlinear Multiobjective Model-predictive Control for Wastewater Treatment Process,Journal of Process Control, 2014. 24(3): 47-59.

[20] Han Honggui, Qiao Junfei, Chen Qili. Model Predictive Control of Dissolved Oxygen Concentration Based on a Self-organizing RBF Neural Network,Control Engineering Practice, 2012, 20(4): 465-476.

II.Patents

[01]Han Honggui, Guo Yanan, Qiao Junfei. Method for Effluent Total Nitrogen Based on a Recurrent Self-organizing RBF Neural Network.US 10570024 B2.

[02]Han Honggui, Guo Yanan, Qiao Junfei. An Intelligent Detecting Method for Biochemical Oxygen Demand BOD Based on a Self-organizing Recurrent RBF Neural Network.US 15/186260.

[03]Han Honggui, Qiao Junfei, Zhou Wendong. Measuring Phosphorus in Wastewater Using a Self-organizing RBF Neural Network.US 10539546 B2.

[04] Han Honggui, Zhang Lu, Qiao Junfei. A Multi-objective Real-time Optimal Control Method for Wastewater Treatment Process.ZL 201611248098.8. (in Chinese)

[05] Han Honggui, Chen Zhiyuan, Qiao Junfei. A Tracking Control Method of Dissolved Oxygen Concentration in Wastewater Treatment Process Using T2FNN.ZL 201610900248.2. (in Chinese)

[06] Han Honggui, Guo Yanan, Qiao Junfei. An Intelligent Detection Method of TN Based on Recurrent Self-organizing RBF Neural Network.ZL 201610606146.X. (in Chinese)

[07] Han Honggui, Zhu Shuguang, Qiao Junfei, Guo Min. An Accurate Control Method of Dissolved Oxygen Concentration Based on RBF Neural Network.ZL 201611022780.5. (in Chinese)

[08]Han Honggui, Zhang Shuo, Hou Ying, Qiao Junfei. An Intelligent Detection Method of MBR Membrane Permeability Based on Recurrent RBF Neural Network.ZL 201610405933.8. (in Chinese)

[09]Han Honggui, Zhang Lu, Lu Wei, Qiao Junfei.An Energy Consumption Prediction Method of Wastewater Treatment Process Based on Adaptive Regression Kernel Function.ZL 201510921369.0.(in Chinese)

[10]Han Honggui, Ge Luming, Qiao Junfei.A Soft Measurement Technique for Ammonia Nitrogen Concentration Based on Fuzzy Neural Network ZL 201510267158.X.(in Chinese)

[11]Han Honggui, Qiao Junfei.A Soft Measurement Technique for Effluent Total Phosphorus Based on a SOPSO-RBF Neural Network.ZL 201410602859.X.(in Chinese)

[12]Han Honggui, Zhang Lu, Qiao Junfei.An Optimal Control Method for Wastewater Treatment Process Based on the Multi-gradient Descent Algorithm.ZL 201410602860.2.(in Chinese)

[13]Han Honggui, Wang Lidan, Li Yin, Qiao Junfei. A Soft Measurement Technique for Sludge Bulking Based on a Spiking-self-organizing RBF Neural Network.ZL 201410147250.8. (in Chinese)

[14] Han Honggui, Wu Xiaolong, Wang Lidan, Qiao Junfei. The Effluent Total Phosphorus Forecasting Method Based on the Fuzzy Neural Network.ZL 201410117471.0. (in Chinese)

[15] Han Honggui, Wu Xiaolong, Qian Huhai, Qiao Junfei. A Model Method for Constructing the Filamentous Sludge Bulking Index SVI.ZL 201310518067.X. (in Chinese)

[16] Han Honggui, Qian Huhai, Li Yin, Qiao Junfei. A Self-organizing Control Method for Wastewater Treatment Process.ZL 201310456956.8. (in Chinese)

[17] Han Honggui, Wu Xiaolong, Wang Lidan, Qiao Junfei. Multi-objective Model Prediction Control for Wastewater Treatment Process.ZL 201310059053.6. (in Chinese)

[18] Han Honggui, Wu Xiaolong, Wang Lidan, Qiao Junfei. DO Concentration Predictive Control Based on Self-organizing RBF Neural Network.ZL 201310000516.1. (in Chinese)

[19] Han Honggui, Qiao Junfei, Ren Donghong, Yuan Xichun. A Predicting Method forSludge Bulking Index of Wastewater Treatment Process.ZL 201210212531.8. (in Chinese)

[20] Han Honggui, Qiao Junfei, Yuan Xichun. A Soft Measurement Model forSludge Volume Index of Wastewater Treatment Process.ZL 201110318552.3. (in Chinese)

Personal Statement

Honggui Han, professor, Vice Dean of Department ofArtificial Intelligence and Automation, Beijing University of Technology. He has attended the National Natural Science Foundation of Outstanding Youth Science Foundation,Beijing Outstanding Young Scientist, YoungElite Scientists Sponsorship program byChinese Association for Science and Technology, Hong Kong Scholar, BeijingNova, and so on. Moreover, he is theDirector ofEngineering Research Center ofDigital Community,Ministry of Education, IEEE senior member, and so on. Furthermore, he is an editor of many international journals and secretary of many international and domestic academic conferences.

He has developed many innovative methods and practical techniques in the area ofintelligent control theory and engineering, artificial intelligence and civil and environmental engineering. Moreover, he has solved many bottleneck problems in urban wastewater treatment industry. He has presided over more than 10 projects, including theNational Key Research and Development Project, the key project of National Natural Science Foundation of China, the National Natural Science Foundation of Outstanding Youth Science Foundation, the Beijing Ministry of Science and Technology projects, as well as other national and provincial projects. He has published more than 80 academic papers in IEEE Transactions on Industrial Electronics, IEEE Transactions on Cybernetics, Automatica and other journals, which have been cited more than 1000 times (SCI index). Moreover, he has written one book, applied for 65 patents (including42 authorized), and authorized 33 software copyrights. Last but not least, he has won many honors, such as the2nd prize of National Science and Technology Progress Award, the1st prize of Chinese Industry University Research Cooperation Award, and the1st prize of Chinese Artificial Intelligence Science and Technology ProgressAward,and so on.