Model-Free Predictive Current Controller for Voltage Source Inverters Using ARX Model and Recursive Least Squares

This work proposes a model-free deadbeat predictive controller (MF-DPC) for voltage source inverters. The proposed control scheme does not require knowledge of the system parameters for its correct operation. This is performed using an auto-regressive with exogenous input (ARX) model with a recursive least squares (RLS) estimation algorithm for parameter identification to represent the physical system. A state-space predictive model using the identified parameters and the past data measurements is established to calculate the inverter voltage reference using the deadbeat control principle and generate it using space vector modulation (SVM) allowing fixed-switching operation. In addition, the inherent sensitivity of the deadbeat controller to parameter mismatches is avoided. Simulation and experimental results confirm the validity of the proposed model-free control approach in terms of tracking accuracy and waveform quality.

• model-free control
• deadbeat predictive control
• voltage source inverter
• ARX model
• recursive least squares
• parameter estimation
• space vector modulation
• constant switching frequency
• parameter mismatch robustness
• current control

• 9 — Industry, innovation and infrastructure

• Multilevel Inverters and Converters
• Advanced Control Systems Optimization
• Sensorless Control of Electric Motors
• model-free control
• deadbeat predictive control
• voltage source inverter
• ARX model
• recursive least squares
• parameter estimation
• space vector modulation
• constant switching frequency
• Electrical and Electronic Engineering
• Control and Systems Engineering
• Engineering