Fuzzy control of synchronous buck converters utilizing fuzzy inference system for renewable energy applications

Abstract

In the present research, an innovative fuzzy control approach is developed specifically for synchronous buck converters utilized in renewable energy applications. The proposed control strategy effectively manages load changes, nonlinear loads, and input voltage variations while improving both stability and transient response. The method employs a fuzzy inference system (FIS) that integrates adaptive control, feedforward control, and multivariable control to guarantee optimal performance under a wide range of operating conditions. The design of the control scheme involves formulating a rule base connecting input variables to an output variable, which signifies the duty cycle of the switching signal. The rule base is configured to dynamically modify control rules and membership functions in accordance with load conditions, input voltage fluctuations, and other contributing factors. The performance of the control scheme is evaluated in comparison to conventional techniques, such as proportional integral derivative (PID) control. Results indicate that the advanced fuzzy control approach surpasses traditional methods in terms of voltage regulation, stability, and transient response, particularly when faced with variable load conditions and input voltage changes. As a result, this control scheme is highly compatible with renewable energy systems, encompassing solar and wind power installations where input voltage and load conditions may experience considerable fluctuations. This research highlights the potential of the proposed fuzzy control approach to significantly enhance the performance and reliability of renewable energy systems.