Wang，Yujuan, Professor of Chongqing University, China
She received her Ph.D. degree in control theory and control engineering from Chongqing University, Chongqing, China, in 2016. She is currently the Professor of the School of Automation, Chongqing University, Chongqing, China.
Prof. Wang has made original contributions in Distributed control and Finite-time control theory with engineering applications, which can be assessed by her publications (over 30 papers) in prestigious international journals, including IEEE T-AC, AUTOMATICA, IEEE T-NNLS, IEEE T-CYB, IEEE T-IE. She authored/co-authored 2 books in the field of finite-time control theory.
Contact Information
Email: yjwang66@cqu.edu.cn
Address:Shazheng Street174#, Shapingba District,Chongqing, 400044,China
Education
Ph.D., Chongqing University, P. R. China, 2016.
M.S., Jiangsu University, P. R. China, 2011.
B.S., Langfang Normal University, P. R. China, 2007.
Academic Experience
Professor, 3/2018- present, Chongqing University, Chongqing, P. R. China
Research assistant, 3/2017-2/2018, The University of Hong Kong, Hong Kong
Visiting Scholar, 9/2014 – 9/2015, University of Texas at Arlington, Arlington
Research Interests
Distributed Control
Finite-time Control
Nonlinear Control
Publications
Part I – Books
[1] Cooperative Control of Nonlinear Networked Systems--Infinite-time and Finite-time Design Approaches, Springer, 2019.
Part II – Referred Journal Papers (selected)
[1] Yongduan Song*, Yujuan Wang, & Changyun Wen. Adaptive fault-tolerant PI tracking control with guaranteed transient and steady-state performance, IEEE Transactions on Automatic Control, vol. 62, no. 1, pp. 481- 487, Jan. 2017.
[2] Yujuan Wang*, Yongduan Song, Miroslav Krstic, & Changyun Wen. Fault-tolerant finite time consensus for multiple uncertain nonlinear mechanical systems under single-way directed communication interactions and actuation failures, Automatica, vol. 63, pp. 374-383, Jan. 2016.
[3] Yongduan Song*, Yujuan Wang, John Holloway, & Miroslav Krstic. Time-varying feedback for regulation of normal-form nonlinear systems in prescribed finite time, Automatica, vol. 83, pp. 243-251, Sep. 2017.
[4] Yujuan Wang*, Yongduan Song. Leader-following control of high-order multi-agent systems under directed graphs: Pre-specified finite time approach, Automatica, vol. 87, pp. 113-120, Jan. 2018.
[5] Yujuan Wang*, Yongduan Song. A general approach to precise tracking of nonlinear systems subject to non-vanishing uncertainties, Automatica, vol. 106, pp. 306-314, Aug. 2019.
[6] Yujuan Wang, Yongduan Song*, & Frank L. Lewis. Robust adaptive fault-tolerant control of multi-agent systems with uncertain non-identical dynamics and undetectable actuation failures, IEEE Transactions on Industrial Electronics, vol. 62, no. 6, pp. 3978-3988, 04 February 2015.
[7] Yujuan Wang*, Yongduan Song, David J. Hill, Zero-error consensus tracking with pre-assignable convergence for non-affine multi-agent systems, IEEE Transactions on Cybernetics, vol.51, no.3, pp.1300-1310, March 2021.
[8] Yongduan Song, Liu He, Yujuan Wang* Globally exponentially stable tracking control of self-restructuring nonlinear systems, IEEE Transactions on Cybernetics, DOI:10.1109/TCYB.2019.2951574.
[9] Yujuan Wang, Yongduan Song*, & Miroslav Krstic. Collectively rotating formation and containment deployment of multi-agent systems: a polar coordinate based finite time approach, IEEE Transactions on Cybernetics, vol.47, no.8, pp.2161-2172, Aug. 2017.
[10] Yujuan Wang, Yongduan Song, David J. Hill, Miroslav Krstic, Prescribed-time consensus and containment control of networked multi-agent systems, IEEE Transactions on Cybernetics, vol. 49, no. 4, pp. 1138-1147, Apr.2019.
[11] Yujuan Wang, Yongduan Song*. Fraction Dynamic-Surface-based Neuroadaptive Finite-Time Containment Control of Multiagent Systems in Nonaffine Pure-feedback Form, IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 3, pp. 678 - 689, March 2017.
[12] Yujuan Wang, Yongduan Song*, & Wei Ren. Distributed adaptive finite time approach for formation-containment control of networked nonlinear systems under directed topology, IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 7, pp.3164-3175. July 2018.
[13] Yujuan Wang, Yongduan Song*, Miroslav Krstic, & Changyun Wen. Adaptive finite time coordinated consensus for high-order multi-agent systems: adjustable fraction power feedback approach, Information sciences, vol. 372, pp.392-406, Dec. 2016.
[14] Ruizhen Gao, Yujuan Wang*, Junfeng Lai, & Hui Gao. Neuro-adaptive fault-tolerant control of high speed trains under traction-braking failures using self-structuring neural networks, Information sciences, vol. 367-368, pp. 449–462, Nov. 2016.
[15] Yujuan Wang, Yongduan Song*, Hui Gao, Frank L. Lewis. Distributed fault-tolerant control of virtually and physically interconnected systems with application to high speed trains under traction/braking failures, IEEE Transactions on Intelligent Transportation Systems, vol.17, no.2, pp.535-545, Feb.2016.
[16] Yongduan Song, Yujuan Wang*, Miroslav Krstic, Time-varying feedback for stabilization in prescribed finite time, International Journal of Robust and Nonlinear Control, vol. 29, no. 3, pp. 618-633, 25 March 2018.
Part III- Conference Papers
[1] Yongduan Song*, Yujuan Wang, John Holloway, & Miroslav Krstic, Time-Varying Feedback for Finite-Time Robust Regulation of Normal-Form Nonlinear Systems, 2016 IEEE 55th Conference on Decision and Control (CDC), 12-14 Dec. 2016: 3837-3842.
[2] Yujuan Wang, Yongduan Song*, David J. Hill, & Miroslav Krstic, Prescribed finite time consensus of networked multi-agent systems, 2017 IEEE 56th Conference on Decision and Control (CDC), 2017, 4088-4093.
[3] Yujuan Wang, Yongduan Song*, & David J. Hill, Zero-error consensus tracking of uncertain nonlinear multi-agent systems, The 57th Conference on Decision and Control (CDC), 2018.
Awards/Honors
· Excellent Doctoral Dissertation Award of Chinese Association of Automation, 2018
· Excellent Doctoral Dissertation Award of Chongqing, 2018
· Excellent Doctoral Dissertation Award of Chongqing University, 2018
