Search

Predictive errors restrict high performance of finite control set model predictive control (FCS-MPC) in the cascaded H-bridge multilevel inverter.In order to solve this problem, the influence mechanisms of parameter mismatch, model discretization, and sampling error on voltage and current prediction errors are analyzed in this article. A hierarchical multifactorial error correction method is proposed. The known voltage prediction errors of the previous adjacent prediction periods are first fed back to calculate the voltage predictive error factors and self-correct the next voltage prediction errors. And then the current prediction errors are calibrated by the corrected voltage and the calculated current predictive error factor. This proposed method involves a simple structure and a good inhibitory ability on multifactorial prediction errors. Finally, experimental results in a three-phase five-level cascaded H-bridge multilevel inverter support the theoretical analysis and the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes an effective sliding mode controller (SMC) for a grid-connected 7-level packed U-cell (PUC7) inverter. The aim is to design a simple controller that deals effectively with the complex control problem of the PUC7 inverter (multiobjective control problem). The selection of the control actions is achieved according to the system state error at every sampling time, regardless of the previous values, which makes the control technique model-independent. The control algorithm evaluates online two cost functions (one for each state error), which are derived on the basis of sliding mode theory, and it selects the optimal control input in order to satisfy the reaching conditions of the two cost functions. Compared with the existing solutions, the proposed SMC technique ensures lower average switching frequency by tuning the hysteresis bandwidth of the capacitor-voltage error. The fast implementation, needless of gains tuning, and simple design procedure are the main features of the proposed algorithm. Simulation and experimental results are presented to prove the effectiveness of the proposed technique in controlling the PUC7 inverter with high dynamic performance and robustness against disturbances and parameters mismatch. [ABSTRACT FROM AUTHOR]

Droop control is broadly used in dc power distribution systems, e.g., dc microgrids. Implementing droop control for switch mode power supplies requires the measurement of average current. Synchronous sampling is used in digital control systems to obtain the average of a triangular inductor waveform. However, the dead time, semiconductor turn-on and turn-off delays, and signal conditioning delays shift the sensed waveform and change the effective duty cycle, resulting in a misalignment and measurement error from the average value. This paper proposes a duty cycle weighted averaging method based on double sampling. By sampling twice per switching period and averaging the results using duty cycle as the weighting factor, the error due to waveform misalignment is theoretically eliminated. The result always equals the average value of the triangle. This method does not rely on the knowledge of circuit delays, making it easy to implement and robust to parameter variations. Simulations and experimental measurements validate the superior performance compared with conventional single and double sampling methods. The experiment on a droop-controlled dc–dc converter demonstrates a more accurate droop characteristic. [ABSTRACT FROM AUTHOR]

To solve the problem of poor robustness due to the high dependence of model predictive control (MPC) on the three-phase inverter model, the influence mechanism of the mismatch of circuit parameters R and L, the model discretization error, and sampling errors on MPC prediction error are analyzed in this paper. A feedback self-correction is proposed, which the next current errors are predicted and used to modify the model, based on the previous prediction errors. This proposed method involves simple structure and a small amount of calculation. Steady-state effects of the proposed method are quantized to prove a good inhibitory ability on multifactorial prediction errors. Finally, experimental results in a three-phase inverter are presented to support the theoretical analysis and demonstrate the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

The current reconstruction strategies using single current sensor in the motor drives are widely researched. However, the sampled currents do not represent the average values within the modulation period, especially for the asymmetric modulation or asymmetric sampling solutions. This is due to the following two reasons: 1) The detected current values obtained at different sampling points are utilized to calculate the three-phase currents; and 2) the detected instantaneous currents are applied to estimate the average current values. In this letter, the current change rates under different action vectors are estimated to compensate these errors in a three-phase four-switch interior permanent magnet synchronous motor (IPMSM) drive with single current sensor. The effectiveness of the proposed strategy is verified by experimental results on a 5-kW IPMSM motor prototype, which shows that the current reconstruction errors are reduced after compensation. [ABSTRACT FROM AUTHOR]