Fen Wu

Professor

  • 919-515-5268
  • Engineering Building III (EB3) 3254
  • Visit My Website

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.

Education

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.

Publications

Cooperative output regulation of multi-agent systems with switched leader dynamics
Yuan, C. Z., & Wu, F. (2018), International Journal of Systems Science, 49(7), 1463-1477.
Stability analysis and controller design for a novel nonlinear system: Fuzzy parameter varying system
Zhang, H. Y., Ban, X. J., & Wu, F. (2018), Journal of Intelligent & Fuzzy Systems, 34(6), 4387-4395.
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.
Cooperative output regulation of multi-agent systems with switched leader dynamics via smooth switching
Yuan, C. Z., Wu, F., & Duan, C. (2017), (Proceedings of the ASME 10th Annual Dynamic Systems and Control Conference, 2017, vol 2, ).
Dynamic output feedback control for continuous-time T-S fuzzy systems using fuzzy lyapunov functions
Liu, Y., Wu, F., & Ban, X. J. (2017), IEEE Transactions on Fuzzy Systems, 25(5), 1155-1167.
Consensus for multi-agent systems with time-varying input delays
Yuan, C. Z., & Wu, F. (2017), International Journal of Systems Science, 48(14), 2956-2966.
Almost output regulation of switched linear dynamics with switched exosignals
Yuan, C. Z., & Wu, F. (2017), International Journal of Robust and Nonlinear Control, 27(16), 3197-3217.
Dynamic output feedback control for continuous-time T-S fuzzy systems using fuzzy Lyapunov functions
Liu, Y., Wu, F., & Ban, X. J. (2017), IEEE Transactions on Fuzzy Systems, 25(5), 1155-1167.
Time-based switching control of genetic regulatory networks: Toward sequential drug intake for cancer therapy
Oduola, W. O., Li, X. F., Duan, C., Qian, L. J., Wu, F., & Dougherty, E. R. (2017), Cancer Informatics, 16.
Time-based switching control of genetic regulatory networks: toward sequential drug intake for cancer therapy
Oduola, W. O., Li, X. F., Duan, C., Qian, L. J., Wu, F., & Dougherty, E. R. (2017), Cancer Informatics, 16.

View all publications via NC State Libraries

View publications on Google Scholar

Grants

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)