A Novel Control Algorithm for DC Motors Supplied by PVs Using Fuzzy Cognitive Networks

Photovoltaic (PV) arrays present non-linear I-V curves, which strongly depend on ambient temperature and solar insolation. This fact poses a problem in identifying the maximum PV power point. In this paper, a dc motor is powered by a PV array and an attempt is made to optimize the use of the PV energy while the DC motor is supplied with suitable current and voltage in order to match its load-speed characteristics. This is achieved through a dc/dc converter controlled by a fuzzy cognitive network (FCN), in parallel with an energy storage device (battery), so that the PV energy is always fully exploitable. The algorithm method uses an FCN and a fuzzy controller, which recognize the maximum power of the PV array very fast while at the same time, they control the speed of the dc motor, under different insolation and temperature conditions. The proposed algorithm is validated through the simulation studies and is proven to be effective.