李敏

发布人:jxxx发表时间:2017-03-05点击:

李敏教授,硕士/博士生导师,湖北省人才计划入选者,地大学者青年拔尖人才,IEEE Member19907生,2012年获华中科技大学工学学士学位,2017年获清华大学工学博士学位,2021年评为中国地质大学(武汉)教授。主持国家自然科学基金面上、青年项目各1项,湖北省自然科学基金青年项目1项;主持其他省部级/横向科研项目4项;累计科研经费200余万元。参与国家02科技重大专项课题“光刻机双扫描硅片台掩模台样机研发与集成”、“磁悬浮工件台关键技术研究”等。发表学术论文20余篇,其中IEEE T-IIIEEE T-IE等国际顶级期刊第一作者论文10篇,SCI他引164次,一作单篇最高SCI他引34次;授权发明专利4项;研究成果已成功应用于国内自主研发的65nm光刻机。受邀国际会议作大会报告1次、担任程序委员会主席3次;担任IEEE T-MECHMSSP等期刊审稿人。

联系方式:

E-mailminli@cug.edu.cn

办公地点:中国地质大学(武汉)机械与电子信息学院(教二楼)339

主要经历

2021.06-至今,中国地质大学(武汉),机电学院,机械工程系,教授

2017.07-2021.05:中国地质大学(武汉),机电学院,机械工程系,副教授

2012.09-2017.06:清华大学,机械工程专业,获工学博士学位

2008.09-2012.06:华中科技大学,机械设计制造及其自动化专业,获工学学士学位

研究方向

[1] 精密/超精密动力学建模:围绕集成电路制造装备、数控机床、机器人等中的精密/超精密运动系统,揭示“力--磁”多物理场耦合、刚柔耦合机理,研究参数化动力学建模方法。

[2] 机器视觉与精密测量:针对精密加工与测量装备微/纳米精度的测量、定位与识别需求,基于机器视觉、激光干涉等技术,研究高精度、多维测量新技术及其在工程中的应用。

[3] 精密/超精密运动控制:针对精密/超精密运动系统接近物理极限的性能指标要求、复杂的动力学特性与多源扰动,基于数据驱动控制理论,研究解耦控制、反馈控制、前馈控制及扰动抑制方法。

[4] 微纳操控机器人:基于智能材料以及微纳米尺度的动力学、表征与控制技术,研究电磁、静电、电热、压电、光电等驱动方式的微纳操控机器人。

招生要求

本课题组欢迎热爱科学研究,对机器视觉、先进控制、精密机电系统感兴趣,具有良好专业基础与实践动手能力的机械、控制、计算机、测控、电机电气等专业硕士生和博士生。本课题组研究生有机会前往清华大学、北京华卓精科等单位学习与锻炼。

科研项目

[1] 国家自然科学基金面上项目,柔性磁浮平面电机多场刚柔耦合建模与模态解耦控制研究52275072),2023.01-2026.12 54万,主持。

[2] 国家自然科学基金青年项目,基于数据驱动的大行程超精密工作台多变量控制研究(51805496),2019.01-2021.1227万,主持。

[3] 湖北省自然科学基金青年项目,光刻机超精密运动台数据驱动多变量控制(2019CFB206),2019.01-2020.125万,主持。

[4] 企事业单位委托项目,数据驱动非线性控制技术及其应用系统开发,2018.08-2022.12100万,主持。

[5] 企事业单位委托项目,三坐标扫描实验台研制,2020.11-2021.1114万,主持。

[6] 航天科学技术基金项目,基于动态线性化无模型自适应控制的高超声速飞行器制导控制一体化研究,2018.06-2019.068万,主持。

[7] 中央高校基本科研业务费专项资金资助项目,光刻机超精密工件台运动控制研究(CUG170667),2017.07-2020.0735万,主持。

[8] 国家科技重大专项02专项课题,光刻机双扫描硅片台掩模台样机研发与集成(2009ZX02208-001),2012.09-2016.04,参与。

[9] 国家科技重大专项02专项课题,磁悬浮工件台关键技术研究(2012ZX02702-006),2012.09-2017.07,参与。

代表性论文

[1] M. Li, J. Xiong, R. Cheng, Y. Zhu, K. Yang, and F. Sun. Rational Feedforward Tuning Using Variance-Optimal Instrumental Variables Method Based on Dual-Loop Iterative Learning Control. IEEE Transactions on Industrial Informatics, 2022, Early Access, DOI: 10.1109/TII.2022.3166590. (1, IF: 11.65)

[2] M. Li, T. Chen, R. Cheng, K. Yang, Y. Zhu, and C. Mao. Dual-Loop Iterative Learning Control With Application to an Ultraprecision Wafer Stage. IEEE Transactions on Industrial Electronics, 2022, 69(11): 11590-11599. (1, IF: 8.16)

[3] M. Li, C. Mao, Y. Zhu, K. Yang, and X. Li. Data-Based Iterative Dynamic Decoupling Control for Precision MIMO Motion Systems. IEEE Transactions on Industrial Informatics, 2020, 16(3): 1668-1676. (1, IF: 11.65)

[4] M. Li, Y. Zhu, K. Yang, L. Yang, and C. Hu. Data-Based Switching Feedforward Control for Repeating and Varying Tasks: With Application to an Ultraprecision Wafer Stage. IEEE Transactions on Industrial Electronics, 2019, 66(11): 8670-8680. (1, IF: 8.16)

[5] M. Li, Y. Zhu, K. Yang, L. Yang, C. Hu, and H. Mu. Convergence Rate Oriented Iterative Feedback Tuning with Application to an Ultraprecision Wafer Stage. IEEE Transactions on Industrial Electronics, 2019, 66(3): 1993-2003. (1, IF: 8.16)

[6] M. Li, K. Yang, Y. Zhu, H. Mu, and C. Hu. State/Model-Free Variable-Gain Discrete Sliding Mode Control for an Ultraprecision Wafer Stage. IEEE Transactions on Industrial Electronics, 2017, 64(8): 6695-6705. (1, IF: 8.16)

[7] M. Li, Y. Zhu, K. Yang, C. Hu, and H. Mu. An Integrated Model-Data-Based Zero-Phase Error Tracking Feedforward Control Strategy with Application to an Ultraprecision Wafer Stage. IEEE Transactions on Industrial Electronics, 2017, 64(5): 4139-4149. (1, IF: 8.16)

[8] M. Li, Y. Zhu, K. Yang, and C. Hu. A Data-Driven Variable-Gain Control Strategy for an Ultra-Precision Wafer Stage with Accelerated Iterative Parameter Tuning. IEEE Transactions on Industrial Informatics, 2015, 11(5):1179-1189. (1, IF: 11.65)

[9] M. Li, C. Mao, M.-F. Ge, and J. Gan. Data-Driven Iterative Feedforward Control with Rational Parametrization: Achieving Optimality for Varying Tasks. Journal of the Franklin Institute, 2019, 365(12): 6352-6372. (2, IF: 4.25)

[10] M. Li, T. Yan, C. Mao, L. Wen, X. Zhang, and T. Huang. Performance-enhanced iterative learning control using a model‐free disturbance observer. IET Control Theory and Applications, 2021, DOI: 10.1049/cth2.12096. (3, IF: 2.67)

[11] M. Li, S. Tan, J. Xiong, J. Gan, and X. Zhang. Model-free output feedback discrete sliding mode control with disturbance compensation for precision motion systems. IET Control Theory and Applications, 2020, 14(14), 1867-1876. (3, IF: 2.67)

[12] M. Li.  Data-Driven Control for Precision Motion Stages, Keynote Speaker, 2019 3rd IEEE International Conference on Robotics and Automation Sciences, Wuhan, 2019-6-12019-6-3 (会议特邀报告)

[13] X. Zhang, M. Li, H. Ding, and X. Yao. Data-driven tuning of feedforward controller structured with infinite impulse response filter via iterative learning control. IET Control Theory and Applications, 2019, 13(8): 1062-1070.

[14] W. Huang, K. Yang, Y. Zhu, X. Li, H. Mu, and M. Li. Data-driven rational feedforward tuning: With application to an ultraprecision wafer stage. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 2020, 234(6): 748-758.

[15] T. Huang, K. Yang, C. Hu, Y. Zhu, and M. Li. Integrated robust tracking controller design for a developed precision planar motor with equivalent disturbances. IET Control Theory and Applications, 2016, 10(9):1009-1017.

[16] W. Huang, K. Yang, Y. Zhu, X. Li, H. Mu, and M. Li. Data-driven rational feedforward tuning: With application to an ultraprecision wafer stage. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 2020, 234(6): 748-758.

[17] Q. Tang, F. Guo, T. Huang, K. Yang, Y. Zhu, and M. Li. Modal-Decomposition-Dependent State-Space Modeling and Modal Analysis of a Rigid-Flexible, Coupled, Multifreedom Motion System: Theory and Experiment. Shock and Vibration, 2020: 8859222.

[18] D. Yu, Y. Zhu, K. Yang, C. Hu, and M. Li. A time-varying Q-filter design for iterative learning control with application to an ultra-precision dual-stage actuated wafer stage. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 2014, 228(9):658-667.

[19] M. Li, Y. Zhu, K. Yang, C. Hu, and H. Mu. A Variable-Gain Discrete Sliding Mode Control Strategy with PID-Type Sliding Surface for an Ultra-Precision Wafer Stage. Proceedings of the ASME 2016 International Mechanical Engineering Congress & Exposition, Phoenix, USA, 2016: V04BT05A037.

[20] M. Li, K. Yang, Y. Zhu, and C. Hu. Optimal zero phase error tracking feedforward control for an ultra-precision dual-stage actuated wafer stage. Proceedings of ASPE 2014 Annual Meeting, Boston, USA, 2014: 226-231.

[21] X. Zhang, M. Li, H. Ding. Adaptive iterative learning control of fluidic muscle driven parallel manipulators for force control with sliding mode technique. Proceedings of the ASME 2020 International Mechanical Engineering Congress & Exposition, Portland, USA, 2020.

[22] D. Yu, Y. Zhu, K. Yang, C. Hu, and M. Li. Combined nonlinear feedback and cascaded iterative learning control for an ultra-precision dual-stage actuated wafer stage. Proceedings of ASPE 2014 Annual Meeting, Boston, USA, 2014: 264-268.

发明专利

[1] 朱煜,张鸣,李敏,等等,动圈式平面电机动子三自由度位移测量方法:中国,CN103292706B

[2] 朱煜,杨开明,李敏,等等,一种动圈式平面电机动子三自由度位移测量方法:中国,CN103292707B

[3] 朱煜,成荣,李敏,等等,一种绝对光栅信号处理方法:中国,CN103560780B

[4] 胡楚雄朱煜汪泽李敏,等等,一种永磁同步直线电机神经网络自适应轨迹跟踪控制方法中国ZL 201610438862.1