LMI-Based MPC Design Applied to the Single-Phase PWM Inverter with LC Filter under Uncertain Parameters.

Area of Science:

• Electrical Engineering
• Control Systems
• Power Electronics

Background:

• Single-phase PWM inverters are crucial for power conversion but susceptible to parametric uncertainties.
• Ensuring stable and accurate sinusoidal output under varying conditions (inductance, load) is a key challenge.
• Existing control methods may struggle with robustness against these uncertainties.

Purpose of the Study:

• To propose a novel design methodology for predictive control of single-phase PWM inverters.
• To address parametric uncertainties in filter inductance and output load resistance.
• To achieve precise sinusoidal signal tracking at the inverter output.

Main Methods:

• Utilizing predictive control based on the receding horizon principle.
• Formulating the control design using linear matrix inequalities (LMIs).
• Employing convex programming techniques for efficient and optimal solution derivation.

Main Results:

• The LMI-based Model Predictive Control (MPC) effectively tracks sinusoidal reference signals.
• The proposed method demonstrates robust disturbance rejection against input voltage and load perturbations.
• Simulations using MATLAB-Simulink and FPGA-in-the-loop confirm the control system's viability and performance.

Conclusions:

• The LMI-based MPC offers an effective solution for controlling PWM inverters with parametric uncertainties.
• The methodology ensures reliable sinusoidal signal generation despite variations in system parameters.
• This approach enhances the robustness and performance of single-phase inverters in practical applications.