Min Wang (IEEE Member, 2009) received the B.Sc. in mathematics and the M.Sc. degree in applied mathematics from the Bohai University, Jinzhou, China, in 2003 and 2006, respectively, and the Ph.D. degree in system theory from Qingdao University, Qingdao, China, in 2009. She is currently a Professor with the School of Automation Science and Engineering, South China University of Technology, Guangzhou, China. From July to September 2008, she was a visiting student in the Department of Electrical and Computer Engineering, the National University of Singapore, Singapore. From November 2017 to October 2018, she is an academic visitor in the Department of Information Systems and Computing, Brunel University London, Uxbridge, United Kingdom. Her current research interests include dynamic learning, adaptive actor-critic control, adaptive neural control, robot control, stochastic control, nonlinear systems, multi-agent systems, network control systems.

She has authored over 50 journal publications related to neural networks and learning systems, among them over 20 papers are regular papers in IEEE Transactions series, and 8 papers are indexed by ESI highly cited papers. These publications were mainly published in some mainstream international journals including IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Cybernetics, IEEE Transactions on Automatic Control, IEEE/CAA Journal of Automatica Sinica, International Journal of Robust Nonlinear Control, IEEE Transactions on Industrial Informatics. These published papers in the first author have total over 1000 SCI citations and 1500 Google Scholar citations by others, respectively. 

She was a winner of the “Second Prize of Guangdong Provincial Natural Science Award” in 2022, the Guangdong Provincial Outstanding Youth Fund in 2019, the youth talent of Guangdong Tezhi Plan in 2016, and the Excellent Doctoral Dissertations Award of Shandong Province in 2010, and the Outstanding Graduate Award for Technological Innovation of Shandong Province in 2009. She is currently an Associate Editor of three international journals, including IEEE Transactions on Neural Networks and Learning Systems, International Journal of Systems Science, and IEEE ACCESS. She is also a very active reviewer for many international journals.

Doctor of Science, College of Automation and Electrical Engineering, Qingdao University, Qingdao, P.R. China, in 2009.  

Master of Science, College of Mathematics, Bohai University, Jinzhou, P.R. China, in 2006.  ²

Bachelor of Science, College of Mathematics, Bohai University, Jinzhou, P.R. China, in 2003.  

Visiting Student, Department of Electrical and Computer Engineering, the National University of Singapore, Singapore, in 07/2008-09/2008. 

09/2018-Present: Professor, School of Automation Science and Engineering, South China University of Technology, Guangzhou, China. 

11/2017-10/2018: Academic Visitor, Department of Information Systems and Computing, Brunel University London, Uxbridge, United Kingdom. 

09/2012-08/2018: Associate Professor, School of Automation, South China University of Technology, Guangzhou, China. 

07/2009-08/2012: Lecturer, School of Automation, South China University of Technology, Guangzhou, China.

IEEE Transactions on Neural Networks and Learning Systems, 2024-present

International Journal of Systems Science, 2020-present

IEEE ACCESS, 2018-present

The Excellent Doctoral Dissertations Award of Shandong Province, China, 2010.

The Outstanding Graduate Award for Technological Innovation of Shandong Province, China, 2009.

The Most Cited Articles of Fuzzy Sets and Systems in 2009-2013. 

The Science and Technology New Star of Zhujiang, Guangzhou, China, in 2014. 

The youth talent of Guangdong Tezhi Plan, China, in 2016.

The Guangdong Provincial Outstanding Youth Fund, China, in 2019. 

The “Second Prize of Guangdong Provincial Natural Science Award” in 2022.

Deterministic Learning Control for Discrete-Time Nonlinear Systems with Unknown Unmatched Dynamics, Principal Investigator, funded by National Natural Science Foundation of China, 2023-2026. 

Deterministic Learning Control for Nonlinear Systems with State Constraints and Its Applications, Principal Investigator, funded by Guangdong Provincial Natural Science Foundation of China, 2019-2023.

Deterministic Learning and Pattern-Based Intelligent Control of Nonlinear Systems with Predefined Performance, Principal Investigator, funded by National Natural Science Foundation of China, 2018-2021. 1

Deterministic Learning and Performance Analysis for Nonlinear Systems in Unknown Dynamic Environments, Principal Investigator, funded by National Natural Science Foundation of China, 2014-2017. 

[1]    Min Wang, Kunning Wang, Longwang Huang, and Haotian Shi,  Observer-based event-triggered tracking control for discrete-time nonlinear systems using adaptive critic design, IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 53, no. 9, pp. 5393-5403, September 2023.

[2]    Haotian Shi, Min Wang, and Cong Wang, Neural Learning Control for Discrete-Time Strict-Feedback Systems: An Error Estimate Method, IEEE Transactions on Circuits and Systems--II: Express Briefs, vol. 70, no. 9, pp. 3439-3442, September 2023.

[3]    Min Wang, Zixin Lin, Cong Wang, Chenguang Yang. Deterministic learning control of manipulators with closed architecture based on outer-loop speed compensation. Acta Automatica Sinica, vol. 49, no. 9, pp. 1904-1914, September 2023.

[4]    Lixue Wang, Min Wang, and Wenchao Meng, System transformation-based event-triggered fuzzy control for state constrained nonlinear systems with unknown control directions, IEEE Transactions on Fuzzy Systems, vol. 31, no. 7, pp. 2331-2344, July 2023.

[5]    Haotian Shi, Min Wang, and Cong Wang, Leader-follower formation learning control of discrete-time nonlinear multiagent systems, IEEE Transactions on Cybernetics, vol. 52, no. 2, pp. 1184-1194, February 2023. 

[6]    Longwang Huang, Min Wang, Filter-based event-triggered adaptive fuzzy control for discrete-Time MIMO nonlinear systems with unknown control gains, IEEE Transactions on Fuzzy Systems, vol. 30, no. 9, pp. 3673-3684, September 2022.

[7]    Min Wang, Haotian Shi, and Cong Wang, Distributed cooperative learning for discrete-time strict-feedback multi agent systems over directed graphs, IEEE/CAA Journal of Automatica Sinica, vol. 9, no. 10, pp.1831-1844, October 2022. 

[8]    Min Wang, Haotian Shi, Cong Wang and Jun Fu, Dynamic learning from adaptive neural control for discrete-time strict-feedback systems, IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 8, pp. 3700 - 3712, August, 2022.

[9]    Min Wang, Longwang Huang and Chenguang Yang. Event-triggered adaptive critic fault-tolerant control for a class of discrete-time MIMO systems, Acta Automatica Sinica, 2022; 48(5):1234-1245.

[10] Min Wang, Fenghua Ou, Haotian Shi, Chenguang Yang and Xiaoping Liu, Model-based adaptive event-triggered tracking control of discrete-time nonlinear systems subject to strict-feedback form, IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 52, no. 7, pp. 4557-4568, July 2022.

[11] Min Wang, Yongtao Zou, and Chenguang Yang, System Transformation-based neural control for full-state-constrained pure-feedback systems via disturbance observer, IEEE Transactions on Cybernetics, vol. 52, no. 3, pp. 1479-1489, March 2022. 

[12] Min Wang, Haotian Shi, Cong Wang and Jun Fu, Neural learning control for discrete-time nonlinear systems in pure-feedback form, SCIENCE CHINA Information Sciences, vol. 65, no. 2, pp. 122206:1-122206:15, Feb. 2022. 

[13] Min Wang, Longwang Huang and Chenguang Yang, NN-based adaptive tracking control of discrete-time nonlinear systems with actuator saturation and event-triggering protocol, IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 12, pp. 7613-7621, Dec. 2021.  

[14] Min Wang, Zidong Wang, Hongli Dong and Qing-Long Han, A novel framework for backstepping-based control of discrete-time strict-feedback nonlinear systems with multiplicative noises, IEEE Transactions on Automatic Control, vol. 66, no. 4, pp. 1484-1496, April. 2021. 

[15] Min Wang, Zidong Wang*, Yun Chen and Weiguo Sheng, Observer-based fuzzy output-feedback control for discrete-time strict-feedback nonlinear systems with stochastic noises, IEEE Transactions on Cybernetics, vol. 50, no. 8, pp. 3766-3777, Aug. 2020.

[16] Min Wang, Zidong Wang*, Yun Chen and Weiguo Sheng, Adaptive neural event-triggered control for discrete-time strict-feedback nonlinear systems, IEEE Transactions on Cybernetics, vol. 50, no. 7, pp. 2946-2958, July. 2020. 

[17] Min Wang, Zidong Wang*, Yun Chen and Weiguo Sheng, Event-based adaptive neural tracking control for discrete-time stochastic nonlinear systems: a triggering threshold compensation strategy, IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 6, pp. 1968-1981, June. 2020. 

[18] Shude He, Min Wang, Shi-Lu Dai, and Fei Luo, Leader-follower formation control of USVs with prescribed performance and collision avoidance, IEEE Transactions on Industrial Informatics, 15(1): 572-581, 2019. 

[19] Min Wang, Anle Yang, Dynamic learning from adaptive neural control of robot manipulators with prescribed performance, IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, no. 8, pp. 2244-2255, Aug. 2017.

[20] Min Wang, Cong Wang, Peng Shi and Xiaoping Liu, Dynamic learning from neural control for strict-feedback systems with guaranteed predefined performance, IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 12, pp. 2564-2576, Dec. 2016.

[21] Shi-Lu Dai, Min Wang, Cong Wang, Neural Learning Control of Marine Surface Vessels With Guaranteed Transient Tracking Performance, IEEE Transactions on Industrial Electronics, vol. 63, no. 3, pp. 1717-1727, Mar. 2016.

[22] Min Wang, Cong Wang, Learning from adaptive neural dynamic surface control of strict-feedback systems, IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 6, pp. 1247-1259, June. 2015.

[23] Min Wang, Xiaoping Liu and Peng Shi, Adaptive neural control of pure-feedback nonlinear time-delay systems via dynamic surface technique, IEEE Transactions Systems, Man and Cybernetics-Part B, vol. 41, no. 6, pp. 1681-1692, Dec. 2011. 

[24] Min Wang, S. S. Ge and Keum-Shik Hong, Approximation-based adaptive tracking control of pure-feedback nonlinear systems with multiple unknown time-varying delays, IEEE Transactions on Neural Networks, vol. 21, no. 11, pp. 1804-1816, Nov. 2010.

[25]   Min Wang, Bing Chen and Peng Shi, Adaptive neural control for a class of perturbed strict-feedback nonlinear time-delay systems, IEEE Transactions on Systems, Man and Cybernetics--Part B, vol. 38, no. 3, pp. 721-730, June. 2008.