Model-Free Predictive Control for Improved Performance and Robustness of Three-Phase Quasi Z-Source Inverters

This paper suggests a novel Model-Free Predictive Control (MFPC) approach for three-phase quasi Z-source inverters (qZSI). While Model Predictive Control (MPC) is popular for qZSI due to its ease of use and performance, it suffers from sensitivity to parameter mismatch. The proposed MFPC overcomes this limitation by relying on an ultra-local model (ULM), eliminating the need for precise parameter matching. This approach establishes a comprehensive mathematical model for key qZSI control variables, including load current, inductor current, and capacitor voltage. Additionally, a unique method seamlessly integrates shoot-through status into the MFPC framework without compromising qZSI operation. Simulation results across various operating conditions demonstrate how much better the suggested MFPC is than the traditional MPC, especially under parameter mismatch scenarios. Notably, the MFPC achieves a significant improvement, exceeding a 37% reduction in total harmonic distortion (THD). Furthermore, the practicality of the proposed MFPC strategy is validated through hardware-in-the-loop (HIL) testing using a C2000TM microcontroller.

• model-free predictive control
• quasi-Z-source inverter
• three-phase inverter
• parameter mismatch robustness
• ultra-local model
• total harmonic distortion reduction
• inductor current control
• capacitor voltage control
• hardware-in-the-loop validation

• 9 — Industry, innovation and infrastructure

• Multilevel Inverters and Converters
• Advanced Control Systems Optimization
• Advanced DC-DC Converters
• model-free predictive control
• quasi-Z-source inverter
• three-phase inverter
• parameter mismatch robustness
• ultra-local model
• total harmonic distortion reduction
• inductor current control
• capacitor voltage control
• Electrical and Electronic Engineering
• Control and Systems Engineering
• Engineering