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Shipboard power management using constrained nonlinear model predictive control

Authors :
Eric R. Westervelt
Jing Sun
Steve Pekarek
Daniel F. Opila
Philip Stone
Hyeongjun Park
James D. Brooks
Ray DeCarlo
Gayathri Seenumani
Source :
2015 IEEE Electric Ship Technologies Symposium (ESTS).
Publication Year :
2015
Publisher :
IEEE, 2015.

Abstract

Both new and existing naval vessels of all sizes face ever-increasing power supply requirements to support advanced mission loads including high power sensors, weapons, and launchers. Adding additional conventional generators to support these loads is infeasible given size and weight constraints and given the pulsed nature of those new loads. Instead, an optimization-based Power Management Controller (PMC) is used to dynamically control power system sources and loads in real time in order to serve system needs with a minimal amount of power supply equipment. In this paper, a Model Predictive Control (MPC) approach is used to dynamically coordinate sources and loads based on future demand. A cost function is used to prioritize various ship goals and objectives, and constraints are added to reflect hardware limitations. A Constrained Nonlinear MPC algorithm is then used to minimize the cost over a finite future horizon and generate control commands in real-time. The PMC is demonstrated to successfully control and improve system performance on a hardware test bed for ship power system research.

Details

Database :
OpenAIRE
Journal :
2015 IEEE Electric Ship Technologies Symposium (ESTS)
Accession number :
edsair.doi...........560a7c41e0bbcfd256ef7e1cf17f7acf