About

Degree(s):

B.S. Electrical Engineering, Michigan State University 2015

Biography:

Connor received a Bachelor of Science in Electrical Engineering from Michigan State University in May 2015. He then began his PhD in Electrical Engineering at Michigan State University in May 2015.

His research interests include the control of multirotor unmanned aerial vehicles, learning based control, model predictive control, and robotic system development. His past research includes dynamic inversion based and feedback linearization based multi-time-scale control strategies for quadrotor UAVs. These strategies use Extended High-Gain Observers (EHGOs) to estimate state tracking error as well as model uncertainty and external disturbances, which are then cancelled by the control design. Other past research includes sensitive parameter selection methods for modeling human head-neck neuromuscular control as well as nonparametric system identification techniques to enable diagnosis of head-neck neuromuscular control deficiencies among patients suffering from neck pain. Connor has also worked to design, build, and validate control circuitry to measure and actively control the temperature of miniature membrane heaters for use in volatile organic compound pre-concentrators for use in MEMS gas sensor development. He also helped design control circuitry for a robotic fish platform to test the efficacy of a fluid conveying fluttering tail propulsion system. He has also worked on developing an online Gaussian field estimator to estimate a field and arrive at the maximum while having a limited number of sensor readings by making tradeoffs between exploration and exploitation. This was implemented on a ground robot to climb a light gradient for verification.