PT Journal
AU Maly, V
   Vesely, M
   Benes, MP
   Neuman, P
   Bukovsky, I
TI Study of Closed-Loop Model Reference Adaptive Control of Smart MicroGrid with QNU and Recurrent Learning
SO Acta Mechanica Slovaca
PY 2017
BP 34
EP 39
VL 21
IS 4
DI 10.21496/ams.2017.034
DE Smart Grids; Microgrids; Diesel Engine Generators (DEG); Photovoltaic panels (PV); Wind Turbine Generators (WTG); Flywheel Energy Storage System (FESS); Battery Energy Storage System (BESS); QNU Controller; Linear and Non-linear Controllers
AB An adaptive quadratic polynomial neural unit (QNU) controller for optimization of a conventional Smart Microgrid control loop is studied and proposed. The parameters associated with the studied grid plants are considered to be known in this study, with the fact that the load is unknown and time-variant. A sample-by-sample real-time recurrent learning algorithm of an additional QNU controller is derived, with its performance tested and discussed as a result of this paper.
ER