Dissertation Defense

Identification and Adaptive Control for High-performance AC Drive Systems

David ReedPhD Candidate

Abstract: High-performance AC machinery and drive systems are used in a variety of applications ranging from robotics to vehicle propulsion. Such applications typically require high-bandwidth and tight regulation of position, speed and/or torque over a wide range of operating conditions. However, machine parameters can vary significantly, degrading the performance of the drive system. While adaptive control techniques can be used to estimate machine parameters online, parameter identification and control are typically conflicting objectives.
In this dissertation, we present research into the development generalizable design methodologies for Simultaneous Identification and Control (SIC) of overactuated systems via case studies with Permanent Magnet Synchronous Machines (PMSMs). Specifically, we propose two different approaches which exploit overactuation to achieve identification and control objectives simultaneously. Finally, the issues of excitation input design and control allocation are addressed by utilizing a receding-horizon control allocation which includes a metric for generating persistently exciting reference trajectories.

Sponsored by


Faculty Host

Heath Hofmann and Jing Sun