Neuro-Fuzzy Controller for a Non-Linear Power Electronic DC-DC Boost Converters - Al-Dabbagh, Zainab Ameer; Shneen, Salam Waley (Universitas Muhammadiyah Yogyakarta, 2024)
The current paper aims to explore the possibility of improving the performance of one of the important systems (boost DC-DC converter) in the field of electrical energy by contributing to the use of electronic power converters to provide the scheduled voltage to the loads with changing operating conditions using traditional (PID control) and expert (Neuro-fuzzy logic control) methods. Test cases are proposed to verify the possibility of improvement and the effectiveness of the system through approved measurement criteria such as improving stability, response time, efficiency, or a performance measure for overshoot and undershoot rates and rise time in addition to steady-state error through which comparison can be made to know the best between the methodology used to evaluate the performance of PID controllers and ANFIS (Adaptive Neuro-fuzzy Inference System). The current paper deals with a study of the operation of non-linear DC-DC Converters with a Neuro-Fuzzy Controller. To verify the system's effectiveness, proposed tests are conducted to simulate operation in real-time. The assumptions adopted are that the input voltage value is available from a direct current source with a voltage of (12) volts, and what is required to supply a load with a voltage ranging between (22-120) depending on the load change. The necessary calculations were made to calculate the converter parameters. The required inductance value was (160μH) and the capacitance value was (276μF). The simulation test was conducted using a model consisting of a resistive load and a step-up converter in addition to the supply source in both the open-loop and closed-loop system states. System tests were also conducted in the presence of the proposed controllers to verify the system's effectiveness.