• laixy@hust.edu.cn
  • 027-87543130
  • WAN Yiming

WAN Yiming is an associate professor with the School of Artificial Intelligence and Automation, Huazhong University of Science and Technology.

Address: 1037 Luoyu Road, Wuhan 430074, China

Research Interests

His research interests include state/parameter estimation, fault diagnosis, industrial data analytics, model predictive control, and fault-tolerant control, with applications in energy, industrial processes, and aerospace.

Lab Publications

1.June 2021: Our paper "Polynomial chaos-based H2 output-feedback control of systems with probabilistic parametric uncertainties" is published online in Automatica. Free download before 31 July.

2.May 2021: Our paper "Real-time energy-efficient optimal control of high-speed electric train" is publised online in Control Engineering Practice.

3.Dec 2020: I give an invited talk on data-driven fault estimation filter design at Academic Salon held by Science China Information Sciences.

4.Oct 2020: Our paper "Battery Parameter Identification Using Recursive Least Squares with Variable Directional Forgetting" is presented at 16th IEEE International Conference on Control & Automation.

5.Jul 2020: Our paper "Probabilistic robust parity relation based fault detection using biased minimax probability machine" is presented at IFAC-V 2020 World Congress.

6.Jun 2020: Our paper "An Unsupervised Fault Detection Method for Railway Turnouts" is accepted for publication in IEEE Transactions on Instrumentation and Measurement.

7.Jan 2020: Our paper "Fault detection for uncertain LPV systems using probabilistic set-membership parity relation" is accepted for publication in Journal of Process Control.

8.Dec 2018: Our paper "Probability-guaranteed set-membership state estimation for polynomially uncertain linear time-invariant systems" is presented at CDC2018 in Miami Beach, US.

9.Jul 2018: Our papers "Robust static H-infinity output-feedback control using polynomial chaos" and "Mixed polynomial chaos and worst-case synthesis approach to robust observer based linear quadratic regulation" are presented at ACC2018, Milwaukee, US.

Copyright © School of Artificial Intelligence and Automation, Huazhong University of Science and Technology. All rights reserved.

South Building 1, HUST, Luoyu Road 1037, Wuhan, Hubei, 430074