OPTIMIZED MPPT CONTROL OF PMSG BASED WECS WITH BOOST CONVERTER USING FUZZY SLIDING MODE CONTROL

Abstract

This thesis presents the study of sophisticated control systems for Permanent Magnet Synchronous Generator (PMSG)-based Wind Energy Conversion Systems (WECS), emphasizing the enhancement of Maximum Power Point Tracking (MPPT) efficacy under fluctuating wind conditions. The system considered in this scholarly thesis consists of Wind Turbine, PMSG, rectifier. DC-DC Boost Converter. MPPT algorithm is used to maximize the output of wind turbine. This MPPT algorithm is used to control the boost converter based on Fuzzy logic control and adjusts the duty cycle of boost converter for optimal output from Wind Turbine. Traditional techniques like Perturb and Observe (P&O) and Sliding Mode Control (SMC) encounter significant constraints, including power fluctuations, losses due to chattering, and reliance on sensors. Traditional techniques, such as Perturb and Observe (P&O) and Sliding Mode Control (SMC), demonstrate significant shortcomings, including power fluctuation, noise losses, and dependence on sensors. This paper presents an innovative hybrid Fuzzy Sliding Mode Control (FSMC) design that combines the resilience of Sliding Mode Control (SMC) with the flexibility of fuzzy logic. The FSMC framework replaces the erratic switching function characteristic of traditional SMC with a 49-rule fuzzy inference system that alleviates fluctuations and diminishes switching losses. The control law changes the sliding surface S(t) dynamically. This allows precise MPPT operation without mechanical sensing (anemometers or tachometers), which cuts the cost of the system by 18–22%. This study is done on the MATLAB Simulink for the simulation and fuzzy logic designing of the PMSG based WECS system.