王玉娟，教授/博导。2016年获重庆大学控制理论与控制工程专业博士学位。
教育背景
2018-2011 江苏大学， 理学硕士
2012-2016 重庆大学，工学博士
2014-2015 德克萨斯大学，访问学者
2017-2018 香港大学， 博士后
专业领域：
控制理论，控制工程
主要研究方向：
多智能体系统协同控制、自适应控制、有限时间控制
主讲课程：
主讲中文硕士及博士课程2门，涵盖智慧工程导论、控制理论进展等。
学术兼职和荣誉：
· 中国自动化学会可信控制系统专业委员会副秘书长
· 担任多个控制领域顶级期刊如IEEE Trans. Automatic Control, Automatica, IEEE Trans. Neural Networks and Learning Systems, IEEE Trans. Industrial Electronics等审稿人
科研情况简介：
长期致力于先进控制理论及应用方面的研究，尤其是在网络化多智能体系统协同控制方面有系列成果，为解决网络化多智能体系统的安全可靠运行提供了创新解决方案，在工业及国防领域有重要应用价值。主持国家自然科学基金重大项目子课题、青年项目、重庆大学百人计划启动基金、中央高校教师科研创新能力提升项目和横向合作项目，参与国家自然科学基金重大项目、973 计划、国际合作项目等。入选重庆大学“百人计划”特聘人才计划。获中国自动化学会优秀博士论文奖（全国十位获奖者之一）、重庆市优秀博士学位论文奖。撰写英文专著1部，编写1部中文书章。目前发表或录用高水平论文30余篇，其中SCI 1区（中科院分区）论文 14篇，SCI 2区论文 6 篇（包括控制领域A类 1篇）。相关研究成果获得国内外专家学者广泛关注及引用评价，引用者包括国内外院士，IEEE Fellow，美国总统奖获得者。
论文及专著：
（一）专著
Yongduan Song, & Yujuan Wang, Cooperative Control of Nonlinear Networked Systems------Nonfinite-time and Finite Time Design Approaches, Springer, 2019.
（二）论文（选录）
[1] Yongduan Song*, Yujuan Wang（王玉娟）, & 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*（王玉娟）, 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（王玉娟）, 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*（王玉娟）, 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*（王玉娟）, 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（王玉娟）, 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*（王玉娟）, 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*（王玉娟）. Globally exponentially stable tracking control of self-restructuring nonlinear systems, IEEE Transactions on Cybernetics, DOI:10.1109/TCYB.2019.2951574.
[9] Yujuan Wang（王玉娟）, 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（王玉娟）, 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（王玉娟）, 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（王玉娟）, 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（王玉娟）, 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*（王玉娟）, 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, 1 Nov. 2016.
[15] Yujuan Wang（王玉娟）, 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*（王玉娟）, 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.
[17] Qian Cui, YujuanWang（王玉娟）, Yongduan Song, Neuroadaptive fault-tolerant control under multiple objective constraints with applications to tire production systems, IEEE Transactions on Neural Networks and Learning Systems, DOI:10.1109/TNNLS.2020.2967150.
[18] Qian Cui, Yujuan Wang（王玉娟）, Yongduan Song, Unified Tracking Control under Full State Constraints Imposed Irregularly, International Journal of Robust and Nonlinear Control, 录用。
[19] Yongduan Song*, Yujuan Wang（王玉娟）, 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.
[20] Yujuan Wang（王玉娟）, 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.
[21] Yujuan Wang（王玉娟）, Yongduan Song*, & David J. Hill, Zero-error consensus tracking of uncertain nonlinear multi-agent systems, The 57th Conference on Decision and Control (CDC), 2018. 21 January 2019. DOI:10.1109/CDC.2018.8618891
[22] Ruizhen Gao, Yujuan Wang*（王玉娟）, Junfeng Lai, Yongduan Song. Self-organizing neural adaptive tracking control of high speed trains subject to unexpected traction-breaking failures, 2016 International Joint Conference on Neural Networks (IJCNN), 2016: 4914-4920.
联系方式：
yjwang66@cqu.edu.cn
重庆市沙坪坝区沙正街174号重庆大学自动化学院
