Nicholas Moehle Advisor: Stephen Boyd |

moehle at stanford dot edu

Ph.D., Mechanical Engineering, Stanford University, in progress

M.S., Electrical Engineering, Stanford University, December 2014

B.S., Mechanical Engineering, University of California, Berkeley, December 2010

My current research involves applying control theory and optimization to power conversion devices.

Maximum Torque-per-Current Control of Induction Motors via Semidefinite Programming. N. Moehle, S. Boyd.

*Proceedings of the Conference on Decision and Control*. Dec 2016.Optimal Current Waveforms for Switched-Reluctance Motors. N. Moehle, S. Boyd.

*Proceedings of the Multi-Conference on Systems and Control*. Sept 2016.A Simple Effective Heuristic for Embedded Mixed-Integer Quadratic Programming. R. Takapoui, N. Moehle, S. Boyd, and A. Bemporad.

*Proceedings of the American Control Conference*. Aug 2016.A Perspective-Based Convex Relaxation for Switched-Affine Optimal Control. N. Moehle, S. Boyd.

*Systems and Control Letters*. Dec 2015.Value Function Approximation for Direct Control of Switched Power Converters. N. Moehle, S. Boyd.

*Working draft*.Optimal Current Waveforms for Brushless Permanent Magnet Motors. N. Moehle, S. Boyd.

*To appear, International Journal of Control*.Covariance Estimation in Two-Level Regression. N. Moehle, D. Gorinevsky.

*Proceedings of SysTol 2013*. Oct 2013.

Principal instructor for:

Convex Optimization I (EE364A), Summer 2016

Teaching assistant for:

Stochastic Control (short course), Winter 2017

Convex Optimization II (EE364B), Spring 2014

Convex Optimization I (EE364A), Winter 2014

Introduction to Linear Dynamical Systems (EE263), Autumn 2013

Introduction to Optimal Control Theory (AA203), Spring 2013

Feedback Control Design (ENGR105), Winter 2013