An intelligent control of photovoltaics is necessary to ensure fast response and high efficiency under different weather conditions. This is often arduous to accomplish using traditional linear controllers, as photovoltaic systems are nonlinear and contain several uncertainties. Based on the analysis of the existing literature of Maximum Power Point Tracking (MPPT) techniques, a high performanc...

This paper deals with the development of a neuro-fuzzy controller for a wind-diesel system composed of a stall regulated wind turbine with an induction generator connected to an ac busbar in parallel with a diesel-generator set having a synchronous generator. A gasifier is capable of converting tons of wood chips per day into a gaseous fuel that is fed into a diesel engine. The controller input...

This paper implements a Neuro-Fuzzy (FNN) approach to autonomously navigate a car-like robot in an unknown environment. The applied technique allows the robot to avoid obstacles and locally search for a path leading to the goal after learning and adaptation. It is based on two Fuzzy Artmap neural networks, a Reinforcement trial and error neural network and a Mamdani fuzzy logic controller (FLC)...

Neuro-fuzzy approaches are developed, in the present work, to determine time-optimal, collision-free path of a car-like mobile robot navigating in a dynamic environment. A fuzzy logic controller (FLC) is used to control the robot and the performance of the FLC is improved by using three different neuro-fuzzy (NN-FLC) approaches. The performances of these neuro-fuzzy approaches are compared amon...