万一鸣

个人信息

Personal information

副研究员    
性别:男
在职信息:在职
所在单位:人工智能与自动化学院
学历:研究生(博士)毕业
学位:工学博士学位
学科:控制理论与控制工程
毕业院校:清华大学
曾获荣誉:
2018年 入选湖北省百人计划
2017年 ISA Transactions 期刊杰出审稿人
2015年 IFAC SAFEPROCESS会议Paul M. Frank最佳理论论文提名奖(1/4)

科学研究

  • Yiming Wan, Tamas Keviczky. “Real-time fault-tolerant moving horizon air data estimation,” IEEE Transactions on Control Systems Technology, DOI: 10.1109/TCST.2018.2804332.


    Yiming Wan, Tamas Keviczky, Michel Verhaegen. “Fault estimation filter design with guaranteed stability using Markov parameters,” IEEE Transactions on Automatic Control, DOI:10.1109/TAC.2017.2742402.


    Yiming Wan, Tamas Keviczky, Michel Verhaegen, Fredrik Gustafsson. “Data-driven robust receding horizon fault estimation,” Automatica, vol. 71, pp. 210-221, 2016. 


    Laura Ferranti,
    Yiming Wan, Tamas Keviczky. “Fault-tolerant reference generation for model predictive control with active diagnosis of elevator jamming faults,” International Journal of Robust and Nonlinear Control, DOI: 10.1002/rnc.4063.


    Yiming Wan, Tamas Keviczky. “Real-time nonlinear receding horizon observer with preestimation for aircraft sensor fault detection and estimation,” International Journal of Robust and Nonlinear Control, DOI: 10.1002/rnc.4011.


    Shouchao Zhai,
    Yiming Wan, Hao Ye. “A set-membership approach to integrated trade-off design of robust fault detection system,” International Journal of Adaptive Control and Signal Processing, vol. 31, pp. 191-209, 2017. 


    Yiming Wan, Wei Wang, Hao Ye,“Integrated design of residual generation and evaluation for 
    fault detection of networked control systems,” International Journal of Robust and Nonlinear Control, vol. 26, no. 3, pp. 519-541, 2016.


    Yiming Wan, Hao Wu, Hao Ye, “Integrated fault detection system design for linear discrete time-varying systems with bounded power disturbances,” International Journal of Robust and Nonlinear Control, vol. 23, no. 16, pp. 1781-1802, 2013.


    Yiming Wan, Fan Yang, Ning Lv, Haipeng Xu, Hao Ye, Weichang Li, Peng Xu, Liming Song, Adam K. Usadi, “Statistical root cause analysis of novel faults based on digraph models”, Chemical Engineering Research and Design, vol. 91, no. 1, pp. 87-99, 2013.


    Yiming Wan, Hao Ye, “Data-driven diagnosis of sensor precision degradation in the presence of control,” Journal of Process Control, vol. 22, no. 1, pp. 26-40, 2012.


    Yiming Wan, Hao Ye, “Integrated trade-off design of fault detection system for linear discrete time-varying systems,” IET Control Theory and Application, vol. 7, no. 3, pp. 455-463, 2013.


    Yiming Wan, Wei Wang, Hao Ye, “Discrete time-varying fault detection filter for non-uniformly sampled-data systems,” Science China Information Sciences, vol. 57, no. 3, pp. 1-11, 2014.


    Yiming Wan, Wei Dong, Hao Ye, “Distributed H1 filtering with consensus strategies in sensor networks: considering consensus tracking error,” Acta Automatica Sinica, vol. 38, no. 7, pp. 1211-1217, 2012.

  • Yiming Wan, Dongying Shen, Sergio Lucia, Rolf Findeisen, Richard D. Braatz. “Robust static H-infinity output-feedback control using polynomial chaos,” 2018 American Control Conference, accepted.


    Yiming Wan, Richard D. Braatz. “Mixed polynomial chaos and worst-case synthesis approach to robust observer based linear quadratic regulation,” 2018 American Control Conference, accepted.


    Yiming Wan, Eranda Harinath, Richard D. Braatz. “A piecewise polynomial chaos approach to stochastic linear quadratic regulation for systems with probabilistic parametric uncertainties,” in Proceedings of the 56th IEEE Conference on Decision and Control, Melbourne, Australia, 2017, accepted.


    Dongying E. Shen, Sergio Lucia,
    Yiming Wan, Rolf Findeisen, Richard D. Braatz. “Polynomial chaos-based H2-optimal static output feedback control of systems with probabilistic parameter uncertainties,” in Proceedings of 20th IFAC World Congress, Toulouse, France, 2017, pp. 3595-3600.


    Yiming Wan, Eranda Harinath, Richard D. Braatz. “Probabilistic robust parity relation for fault detection using polynomial chaos,” in Proceedings of 20th IFAC World Congress, Toulouse, France, 2017, pp. 1042-1047.


    Yiming Wan, Tamas Keviczky. “Implementation of real-time moving horizon estimation for robust air data sensor fault diagnosis in RECONFIGURE benchmark,” IFAC Symposium on Automatic Control in Aerospace, Sherbrooke, Quebec, Canada, 2016.


    Yiming Wan, Tamas Keviczky, Michel Verhaegen. “Robust air data sensor fault diagnosis with enhanced fault sensitivity using moving horizon estimation,” 2016 American Control Conference, Boston, MA, USA, 2016, pp. 5969-5975.


    Laura Ferranti,
    Yiming Wan, Tamas Keviczky. “Predictive flight control with active diagnosis and reconfiguration for actuator jamming,” 5th IFAC Conference on Nonlinear Model Predictive Control, Seville, Spain, 2015, pp. 166-171.


    Yiming Wan, Tamas Keviczky, Michel Verhaegen. “Data-driven sensor fault estimation filter design with guaranteed stability,” 9th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, Paris, France, 2015, pp. 982-987. (Finalist of Paul M. Frank Best Theoretical Paper Award)


    Yiming Wan, Tamas Keviczky. “Fault detection and isolation for air data sensors using realtime moving horizon estimation,” in Proceedings of 2015 AIAA Guidance, Navigation, and Control Conference, Kissimmee, US, DOI: 10.2514/6.2015-1083.


    Yiming Wan, Tamas Keviczky, Michel Verhaegen, “Moving horizon least-squares input estimation for linear discrete-time stochastic systems,” in Proceedings of 19th IFAC World Congress, Cape Town, South Africa, 2014, pp. 3483-3488.


    Yiming Wan, Hao Ye, “Fault detection of networked control systems utilizing limited possibilities of unknown packet transmission,” in Proceedings of 2011 IEEE Conference on Automation Science and Engineering, Trieste, Italy, 2011, pp. 619-624.


    Yiming Wan, Hao Ye, Yongqiang Wang, “Fault detection of networked control systems subject to uncertain time-varying delay and packet dropout,” in Proceedings of the 4th International Conference on Innovative Computing, Information and Control, 2009, pp.231-235.