RESEARCH
My
primary research interests are in three areas, the application of
Model-Based Predictive Control (MPC) methods to nonlinear optimization
problems, the development of game theoretic methods for autonomous
robot trajectory planning and optimization problems associated with
applications in renewable energy. MPC is a receeding horizon
optimization methodolgy which has the advantage of incorporating
constraints explicitly. It has the disadvantage of being
computationally expensive for high order and/or large horizon
problems. MPC is not a recent addition to the field of control
systems although a relatively recent resurgence within the control
sciences community, due in part to advances in computing capability,
has produced some interesting applications-oriented results. My
current work in this area has centered on the applicability of using
MPC methods to generate trajectories for constrained multi-vehicle
coordinated control problems which are optimal under system
uncertainties and various cost criteria. Such problems are
nonlinear due to the dynamics associated with vehicle motion.
EDUCATION
BS 1992
MS 1994 University of Minnesota-Twin Cities
PhD 2005 University of Wisconsin-Madison
FIELDS OF INTEREST
Control Systems, Autonomous Robotics, Optimization, Automotive Powertrain Systems Modeling
FILES AND LINKS OF INTEREST
Drexel University Mathematics Library
CURRENT AND PAST STUDENTS
Sumanth Museboyina - MS (Fall 2011)
Priti Sood - MS (Fall 2011)
Aaron Dahlen - MS (Spring 2012)
Isiah Hoedek - MS (Fall 2014)