Neuro-fuzzy scheme plus optimal PI control for controlling DC-DC converters

Area of Science:

• Renewable Energy Systems
• Control Engineering
• Power Electronics

Background:

• Governments worldwide are prioritizing renewable energy sources like solar power to reduce fossil fuel dependency.
• Improving the efficiency of solar energy systems, particularly the DC-DC converter, is crucial for maximizing energy yield.
• Nonlinear characteristics of solar systems can challenge traditional controllers like PID, necessitating advanced control strategies.

Purpose of the Study:

• To develop and evaluate a novel cascade control scheme for DC-DC converters in solar systems.
• To enhance the dynamic and steady-state performance of solar energy systems.
• To improve the overall efficiency and maximum power point tracking (MPPT) capabilities under varying conditions.

Main Methods:

• A cascade control strategy integrating an optimized Proportional-Integral (PI) controller with a neuro-fuzzy controller was proposed.
• Particle Swarm Optimization (PSO) was employed for efficient tuning of the PI controller's parameters.
• The neuro-fuzzy controller utilized power and current changes as inputs to regulate the duty cycle, directly influencing output voltage.

Main Results:

• The proposed cascade controller demonstrated a significant efficiency improvement of at least 15% for the DC-DC converter compared to a standalone neuro-fuzzy controller.
• The optimized PI controller, with only two tuning parameters, reduced design time while enhancing system responses.
• Integral Square Error (ISE) analysis confirmed minimal tracking errors for both setpoint tracking and disturbance rejection.

Conclusions:

• The integration of an optimized PI controller with a neuro-fuzzy controller offers a superior control solution for solar DC-DC converters.
• The proposed method effectively enhances system efficiency and robustness under diverse environmental conditions.
• This advanced control strategy contributes to more reliable and efficient solar energy harvesting.