ZHAO Kai, Professor of Chongqing University, China

Kai Zhao received the Ph.D. degree in control theory and control engineering from Chongqing University, Chongqing, China, in 2019. He held research positions with Department of Computer and Information Science at University of Macau, and Department of Electrical and Computer Engineering at National University of Singapore. Since 2023 he has been a professor at School of Automation, Chongqing University, China.

His research interests include adaptive control, constrained control, prescribed performance control, and robot control and applications. Dr. Zhao was a recipient of Excellent Doctoral Dissertation Award of Chongqing Municipality in 2020, Excellent Doctoral Dissertation (Nomination) Award of Chinese Association of Automation (CAA) in 2020, and Outstanding Reviewer Award of IEEE Transactions on Cybernetics in 2022.

Contact Information

Telephone: +86-15123353758

Email: zhaokai@cqu.edu.cn; kevin421375@gmail.com

Address: No.55 Daxuecheng South Rd.,Shapingba,Chongqing,401331,China

Education & Academic Experience

2023–to Now  Professor, Chongqing University, China

2021–2023  Research Fellow, National University of Singapore, Singapore

2019–2021  Postdoctoral Fellow, University of Macau, Macau

2017–2018  Visiting PHD Student, The University of Newcastle, Australia

2015–2019  Ph.D., Chongqing University, China

Research Interests

Adaptive and Learning Systems

Prescribed Performance Control

Constrained Control

Publications

Part I – Books

[1] Y. D. Song, K. Zhao, and S. Zhou, Design and Analysis of Nonlinear System Control (in Chinese), Science Press, Beijing, Aug. 2022

Part II – Referred Journal Papers (selected)

[2] L. Li, K. Zhao (corresponding author), Z. Zhang, and Y. D. Song, “Dual-channel event-triggered robust adaptive control of strict-feedback system with flexible prescribed performance,” IEEE Trans. Automatic Control, doi: 10.1109/TAC.2023.3328167, 2023

[3] K. Zhao, F. L. Lewis, and L. Zhao, “Unifying performance specifications in tracking control of MIMO nonlinear systems with actuation faults,” Automatica, 155, Article 111102, 2023

[4] K. Zhao, Y. D. Song, C. L. Philip Chen, and L. Chen, “Adaptive asymptotic tracking with global performance for nonlinear systems with unknown control directions,” IEEE Trans. Automatic Control, 67(3), pp. 1566-1573, 2022

[5] K. Zhao, and Y. D. Song, “Removing the feasibility conditions imposed on tracking control designs for state-constrained strict-feedback systems,” IEEE Trans. Automatic Control, vol. 64, no. 3, pp. 1265-1272, 2019

[6] K. Zhao, Y. D. Song, C. L. Philip Chen, and L. Chen, “Control of nonlinear systems under dynamic constraints: A unified barrier function-based approach,” Automatica, vol. 56, no. 9, pp. 1-9, 2020

[7] K. Zhao, Y. D. Song, and Z. Zhang, “Tracking control of MIMO nonlinear systems under full state constraints: A single-parameter adaptation approach free from feasibility conditions,” Automatica, vol. 55, no. 8, pp. 52-60, 2019

[8] Y. D. Song, K. Zhao, and M. Krstic, “Adaptive control with exponential regulation in the absence of persistent excitation,” IEEE Trans. Automatic Control, vol. 62, no. 5, pp. 2589-2596, 2017

[9] Y. D. Song, B. B. Zhang, and K. Zhao, “Indirect neuroadaptive control of unknown MIMO systems tracking uncertain target under sensor failures,” Automatica, vol. 77, no. 3, pp. 103-111, 2017

[10] Z. Zhang, C. Wen, K. Zhao, and Y. Song, “Decentralized adaptive control of uncertain interconnected systems with triggering state signals,” Automatica, 141:110283, 2022

[11] K. Zhao, Y. D. Song, J. Qian, and J. Fu, “Zero-error tracking control with pre-assignable convergence mode for nonlinear systems under nonvanishing uncertainties and unknown control direction,” Systems & Control Letters, vol. 115, no. 5, pp. 34-40, 2018

[12] K. Zhao, L. Chen, W. Meng, and L. Zhao, “Unified mapping function-based neuro-adaptive control of constrained uncertain robotic systems,” IEEE Trans. Cybernetics, 53(6), pp. 3665-3674, 2023

[13] K. Zhao, and Y. D. Song, “Neuroadaptive robotic control under time-varying asymmetric motion constraints: A feasibility-condition-free approach,” IEEE Trans. Cybernetics, vol. 50, no. 1, pp. 15-24, 2020

[14] K. Zhao, Y. D. Song, and Z. Shen, “Neuro-adaptive fault-tolerant control of nonlinear systems under output constraints and actuation faults,” IEEE Trans. Neural Networks and Learning Systems, vol. 29, no. 2, pp. 286-298, 2018

[15] K. Zhao, Y. D. Song, T. D. Ma, and L. He, “Prescribed performance control of uncertain Euler-Lagrange systems subject to full-state constraints,” IEEE Trans. Neural Networks and Learning Systems, vol. 29, no. 8, pp. 3478-3489, 2018

[16] K. Zhao, Y. D. Song, W. Meng, C. L. Philip Chen, and L. Chen, “Low-cost approximation-based adaptive tracking control of output-constrained nonlinear systems,” IEEE Trans. Neural Networks and Learning Systems, 32(11), pp. 4890-4900, 2021

[17] K. Zhao, and J. W. Chen, “Adaptive neural quantized control of MIMO nonlinear systems under actuation faults and time-varying output constraints,” IEEE Trans. Neural Networks and Learning Systems, vol. 31, no. 9, pp. 3471-3481, 2020

[18] K. Zhao, C. Wen, Y. Song, and F. L. Lewis, “Adaptive uniform performance control of strict-feedback nonlinear systems with time-varying control gain,” IEEE/CAA Journal of Automatica Sinica, 10(2), pp. 1-11, 2023

Awards/Honors

· Top-Notch Young Talents, Chongqing Municipality, 2022

· Outstanding Reviewer, IEEE Trans. Cybernetics, 2022

· Excellent Doctoral Dissertation (Nomination) Award, Chinese Association of Automation, 2020

· Excellent Doctoral Dissertation Award, Chongqing Municipality, 2020

· Excellent Doctoral Dissertation Award, Chongqing University, 2020

· The UM Macao Postdoctoral Fellowship (Class A), University of Macau, 2019