Water demand pattern classification from smart meter data
Sean A. McKenna, Francesco Fusco, et al.
CCWI 2013
Energy-maximizing controllers for wave energy devices are normally based on linear hydrodynamic device models. Such models ignore nonlinear effects which typically manifest themselves for large device motion (typical in this application) and may also include other modeling errors. The effectiveness of a controller is, in general, determined by the match between the model the controller is based on and the actual system dynamics. This match becomes especially critical when the controller is highly tuned to the system. In this paper, we present a methodology for reducing this sensitivity to modeling errors and nonlinear effects by the use of a hierarchical robust controller, which shows small sensitivity to modeling errors, but allows good energy maximization to be recovered through a passivity-based control approach. © 2010-2012 IEEE.
Sean A. McKenna, Francesco Fusco, et al.
CCWI 2013
Francesco Fusco, John V. Ringwood
CCA 2014
Bijay Neupane, Laurynas Siksnys, et al.
e-Energy 2022
Francesco Fusco, Bradley Eck, et al.
ICPR 2014