Adaptive sliding mode control based on maximum power point tracking for boost converter of photovoltaic system under reference voltage optimizer

Abstract

This article presents an innovative APISMC method applied to PVS, integrating the MPPT technique for a boost converter. The primary objective of this approach is to maximize the converter’s output power while ensuring optimal operation in the face of varying environmental conditions such as solar irradiance and temperature, while dynamically adapting to variations in system parameters, as demonstrated by the obtained results. To achieve this, a RVO is employed to generate reference voltage and power. A PI controller calculates the reference current based on this power. The APISMC control modeling utilizes all its reference variables to synthesize the sliding surface and duty cycle for optimal boost converter control. Simulations conducted demonstrate superior performance in terms of stability, speed, and control of the converter compared to traditional MPPT algorithms. The main contributions of this article include an improvement in system robustness against irradiance variations, thanks to the integration of an adaptive algorithm and a PI controller within the SMC. Moreover, the proposed theoretical and practical framework enables rapid MPPT attainment by adjusting the duty cycle in real-time, optimizing maximum power extraction and ensuring stable regulation even under non-ideal conditions.