Improved Continuous Control Set Model Predictive Control for Three-Phase CVCF Inverters: Fuzzy Logic Approach

Abstract

This paper presents an improved continuous control set model predictive control (CCS-MPC) scheme using a fuzzy logic approach (FLA) for three-phase constant voltage constant frequency (CVCF) inverters with an output LC filter. The proposed method can enhance the output voltage quality by using an optimal predictive control law (OPCL). Additionally, the proposed method corrects the input voltage commands through the FLA-based online gain tuning aiming to satisfy the hardware constraint. Thus, the proposed FLA-based CCS-MPC can guarantee an acceptable output voltage with a faster transient response, smaller steady-state error (SSE), and lower total harmonic distortion (THD). Moreover, a Kalman filter-based load current observer is used to significantly improve the reliability and robustness. Comparative experimental studies with another CCS-MPC method are conducted on a prototype three-phase CVCF inverter using TI TMS320F28335 DSP to validate the improved performance under the step-changes of linear/unbalanced/nonlinear loads with uncertain parameters.

Keywords

• Continuous control set model predictive control (CCS-MPC)
• fuzzy logic approach (FLA)
• optimal predictive control law (OPCL)
• three-phase constant voltage constant frequency (CVCF) inverter