Education:

PhD MAE University of California, Los Angeles (expected 2009)

PhD EE Nanyang Technological University, Singapore (2006)

M.S. Harbin Institute of Technology, China (2003)

B.S. Harbin Institute of Technology, China (2001)

Member since:

Email:

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Background Information

I received my Bachelor and Master's degrees from the Harbin Institute of Technology, Harbin, Heilongjiang, P. R. China in 2001 and 2003, respectively, both in the department of Control Science & Engineering. Between August 2003 and December 2005, I have been with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore to pursue my Ph.D. degree. Since January 2006, I am working for Ph.D in the Department of Mechanical and Aerospace Engineering, UCLA. My current research area includes: Modeling and Control of Dynamic Systems with Applications in Mechanical Systems, Digital Control, Repetitive and Learning Control, Adaptive and Optimal Control; Mechatronics.

Current Projects

1. Adaptive Control of Halbach Linear Motor for Nanopositioning
2. A Halbach linear motor control system was setup based on LabVIEW Real-time. Using an FPGA based decoding scheme and sensor signal processing, a nanoscale sensor noise level has been obtained. Adaptive and repetitive control were employed to reject the 60Hz disturbance and its harmonics. The proposed decoding system uses NI LabVIEW FPGA module and multifunction intelligent data acquisition (DAQ) module, NI PXI-7833R, the root-mean-square (RMS) of sensor noise is 0.23nm, which is from a 4 micrometer period sinusoidal quadrature encoder signal, far exceeding the sensitivity requirements.
3. Adaptive Control of Piezoelectric (PZT) Actuator for Nanopositioning
4. The Piezoelectric Nanopositioner was setup based on LabVIEW FPGA. Adaptive feedforward control based on Laguerre filters was applied to track reference trajectory with 100 kHz sampling rate, where the fixed point Least-Mean-Square (LMS) algorithm was implemented on FPGA. The proposed control algorithms requires less filter length compared with conventional FIR LMS algorithm.

Related Publications

1. Yigang Wang and , Kevin C. Chu and Tsu -Chin Tsao, “An Analysis and Synthesis of Internal Model Principle Type Controllers.” Proceedings of American Control Conference, St. Louis, Missouri, 2009.
2. Yigang Wang and , Kevin C. Chu and Tsu -Chin Tsao, “Adaptive Rejection of Stochastic and Deterministic Sinusoidal Disturbances with Unknown Frequency.” Proceedings of American Control Conference, St. Louis, Missouri, 2009.
3. Yigang Wang and , Kevin C. Chu and Tsu -Chin Tsao, “Analysis and Control of Linear Motor for Nanopositioning.” Proceedings of ASME Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power & Motion Control Theme: System Engineering, Hollywood, California, 2009.
4. Yigang Wang and , Kevin C. Chu and Tsu -Chin Tsao, “Adaptive Control for Deterministic Trajectory Tracking and Random Disturbance Rejection with Application to Nano Precision Positioning of a Halbach Linear Motor.” Proceedings of ASME Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power & Motion Control Theme: System Engineering, Hollywood, California, 2009.