An improved model-free predictive current control scheme based on double voltage vector for two-level voltage source inverters (2L-VSIs) is proposed in this article. First, two basic voltage vectors (VVs) are chosen in each control period, whose durations are calculated based on the cost function. Then, a novel current gradient updating method is developed by using the applied two VVs to calculate the current gradients of the remaining six VVs. As a result, the stagnation effect can be eliminated and current ripples and total harmonic distortion can be reduced effectively. In addition, due to the nature of vector diagram symmetry, the processing of current gradient updating is simplified and the calculation speed is increased. The effectiveness of the proposed scheme is verified by simulation and experimental results from the 2L-VSI system.

Model-free predictive current control (MFPCC) methods based on look-up tables (LUTs) have been widely applied in voltage source inverters (VSIs) due to their simple implementation and excellent robustness. However, the performance of the VSIs is affected by the voltage vector used, accuracy of current gradients, and sampling noise. In order to improve these, a new double-vector MFPCC method is proposed in this article. First, a synthetic voltage vector composed of double vectors is applied in each control period to reduce current ripples, where the durations of the double vectors are calculated using predicted current gradients. Next, an extended LUT is designed by using the current gradients of the applied synthetic voltage vectors to update all current gradients of eight basic voltage vectors, so as to increase the accuracy of current gradients. Then, the effect of the sampling noise on MFPCC is analyzed in detail and suppressed by a sliding mode observer for the VSIs. Finally, simulation and experimental results have verified the effectiveness of the proposed method.

Model-free predictive current control (MFPCC) has been widely used in voltage source inverters (VSIs). The output current performance of look-up-table-based MFPCC is affected by the number of the applied voltage vectors (VVs), the current gradient updating and the sampling disturbance. To improve the current performance, a novel modulated MFPCC is proposed for VSI, while real-time current gradient updating and sampling disturbance suppression can be achieved. First, three basic VVs are picked, whose duration time are computed according to the current gradients. Second, an advanced current gradient updating method is presented by establishing the equations of different current gradients under different VVs. Furthermore, the sampling disturbance effect on MFPCC is analyzed and an extended state observer is designed to suppress such effect. Simulation model and experimental platform of the VSI system are structured to verify the preponderance of the proposed MFPCC in reducing the total harmonic distortion of output current.

The parametric uncertainties have a great effect on the output voltage of grid-forming inverters when they are operated under conventional modulated model predictive control (MPC). To address this known issue, a novel modulated model-free predictive control (MFPC) is proposed in this article. First, a new look-up table (LUT) formed by capacitor voltage differences and inductor current differences of LC -filter is designed for voltage-current predictions. Then, the state-space equations of different voltage vectors are established and reconstructed to update each voltage-current difference in the LUT per control period. Next, the duration of each voltage vector and the voltage prediction are calculated based on the updated voltage differences, so as to remove the impact of parameter variation on duration calculation and prediction calculation, enabling their robustness. Finally, the practicality of the proposed approach is demonstrated experimentally under both ideal and mismatched parameters. In comparison with conventional modulated MPC, the proposed modulated MFPC not only achieves comparable voltage performance, but also exhibits greater robustness.

The model predictive control (MPC) is sensitive to parameter variations in LCL -filtered voltage source inverters (VSIs). To improve the robustness of the MPC, this article proposes a parameter-less prediction and reference-based predictive control (PLPR-PC) for LCL -filtered VSIs, where the proposed PLPR-PC not only obtains the parameter-less predictions by measuring and updating all current-voltage gradients but also obtains the parameter-less references by using the phase differences between measured currents and voltages. The proposed PLPR-PC effectively eliminates parametric effects on both prediction and reference calculations and thereby improves the robustness of grid current for LCL -filtered VSIs under parameter variations. The 30-kW simulation and experimental prototype are built up to verify the feasibility and performance of the proposed PLPR-PC.

The modulated model-free predictive control (MFPC) is affected by the noise effect and the parameter mismatch in LC -filtered voltage source inverters (VSIs). To improve the noise suppression capability and parameter robustness of the MFPC, this article proposes a modulated parameter less (PL) prediction and reference-based predictive control with noise suppression (PLPR-PC-NS) for LC -filtered VSIs, where the proposed PLPR-PC-NS not only obtains the modulated PL-prediction by measuring, updating, and filtering all gradients, but also obtains the PL-reference by using the phase angle difference between sampled current and voltage. The proposed PLPR-PC-NS effectively suppresses noise effect on prediction and eliminates parametric effect on reference, improving the capacitor voltage of LC -filtered VSIs. The experimental prototype of LC -filtered VSIs is built up to verify the feasibility and performance of proposed PLPR-PC-NS.