Fen Wu


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  • Engineering Building III (EB3) 3254
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Dr. Wu’s long-term goal is to play an important role in the development of robust and nonlinear control theory. A major roadblock in the development of robust and nonlinear control theory is solvability (computation) and so his work focuses largely on solvability.

Dr. Wu teaches Nonlinear System Analysis and Control (MAE 522). This is a first-year graduate-level course that introduces students to the interesting nonlinear behavior and the corresponding control strategies, like Liapunov stability theory, feedback linearization, and sliding mode control. He also teaches Robust Control with Convex methods (MAE 721). This is an advanced course that goes beyond linear theory to provide modern tools that enhance robustness when the system is not completely known.

At the undergraduate level, Dr. Wu teaches Dynamics of Machines (MAE 315) and Principles of Automatic Control (MAE 435). In both of these courses, Dr. Wu’s major emphasis to the students is that we are dealing with systems and, as such, that they obey systematic methods.

Dr. Wu’s students are theoretically oriented, self-motivated, and work independently. He tends to give them a lot of freedom in their research direction. His students enjoy the subject, among the different reasons, because of its unique blend of mathematics and engineering.

Outside of work, Dr. Wu spends time with his family and enjoys travel.


Ph.D. 1995

Mechanical Engineering

University of California at Berkeley

M.S. 1988

Automatic Control

Beijing University of Aeronautics and Astronautics

B.S. 1985

Automatic Control

Beijing University of Aeronautics and Astronautics

Research Description

Dr. Wu is interested in control theory, robust analysis and control, gain-scheduling control design and implementation, model approximation, structure and control interaction analysis, and the application of advanced control and optimization techniques to aerospace, mechanical and chemical engineering problems. Presently, he is working on fault detection algorithms that improve the safety of hypersonic vehicles (for NASA), and the development of computationally efficient algorithms for nonlinear systems that have polynomial nonlinearities. Within MAE he collaborates with Dr. Buckner and Dr. Yuan.


Fault-Tolerant Attitude Control for Rigid Spacecraft Without Angular Velocity Measurements
Wang, X., Tan, C. P., Wu, F., & Wang, J. (2021), IEEE TRANSACTIONS ON CYBERNETICS, 51(3), 1216–1229. https://doi.org/10.1109/TCYB.2019.2905427
Modeling and Control of Drill-String System With Stick-Slip Vibrations Using LPV Technique
Cheng, J., Wu, M., Wu, F., Lu, C., Chen, X., & Cao, W. (2021), IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 29(2), 718–730. https://doi.org/10.1109/TCST.2020.2978892
Remaining useful life prediction of PEMFC based on cycle reservoir with jump model
Jin, J., Chen, Y., Xie, C., Zhu, W., & Wu, F. (2021), INTERNATIONAL JOURNAL OF HYDROGEN ENERGY. https://doi.org/10.1016/j.ijhydene.2021.09.233
H-infinity observer-controller synthesis approach in low frequency for T-S fuzzy systems
Xie, W.-B., Han, Z.-K., Wu, F., & Zhu, S. (2020), IET CONTROL THEORY AND APPLICATIONS, 14(5), 738–749. https://doi.org/10.1049/iet-cta.2019.0242
Convexified H-infinity output-feedback consensus synthesis for linear multi-agent systems
Xue, X., Yuan, C., & Wu, F. (2019), IET CONTROL THEORY AND APPLICATIONS, 13(11), 1619–1628. https://doi.org/10.1049/iet-cta.2018.5337
Iterative-Learning-Control-Based Tracking for Asteroid Close-Proximity Operations
Long, J., & Wu, F. (2019), JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 42(5), 1195–1203. https://doi.org/10.2514/1.G003884
New Controllability Conditions for Networked, Identical LTI Systems
Hao, Y., Duan, Z., Chen, G., & Wu, F. (2019), IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 64(10), 4223–4228. https://doi.org/10.1109/TAC.2019.2893899
Robust consensus for linear multi-agent systems with structured uncertainties
Xue, X., Wu, F., & Yuan, C. (2019), INTERNATIONAL JOURNAL OF CONTROL. https://doi.org/10.1080/00207179.2019.1612096
Special issue on advanced analysis and control design of switching linear parameter-varying systems and its applications
Zhu, Y., Wu, F., Karimi, H. R., & Lu, B. (2019), PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING, 233(1), 3–4. https://doi.org/10.1177/0959651818819594
Almost output regulation of LFT systems via gain-scheduling control
Yuan, C. Z., Duan, C., & Wu, F. (2018), International Journal of Control, 91(5), 1161–1170. https://doi.org/10.1080/00207179.2017.1309573

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Advanced Switching Control Techniques For Switched Systems Subject to Physical Constraints
National Science Foundation (NSF)(6/01/12 - 8/31/16)
Developing High Performance, Computationally Efficient Nonlinear Control Techniques For Polynomial Nonlinear Systems
National Science Foundation (NSF)(6/01/08 - 5/31/12)
Reconfigurable Robust Gain-Scheduled Control for Air-Breathing Hypersonic Vehicles
National Aeronautics & Space Administration (NASA)(1/05/07 - 12/31/11)
Developing Nonlinear Optimal and Robust Control Techniques for Space Exploration
NCSU NC Space Grant Consortium(7/01/06 - 6/30/07)