Neurofuzzy robust backstepping based MPPT control for photovoltaic system

Abstract

Linear maximum power point tracking (MPPT) techniques are unable to achieve the desired performance and efficiency under wide variation in atmospheric conditions (temperature and irradiance) and consequently the maximum power point (MPP). Hence, the design and implementation of a nonlinear MPPT controller is essential to address the problems associated with the variations of the MPP. In this research article, a new nonlinear robust backstepping-based MPPT control technique is proposed for a standalone PV array connected to a dynamic load, and its performance comparison with existing backstepping, integral backstepping and conventional proportional integral derivative (PID) and perturb and observe (P&O) based MPPT techniques is provided. Simulations, performed in Matlab/Simulink platform, verify the effectiveness of the proposed MPPT technique and demonstrate its superior performance to the backstepping, integral backstepping and conventional MPPT techniques under simultaneous variation in irradiance and temperature and certain faults occurring in the system.