Two-Vector Model Predictive Control Method for Reducing Steady State Tracking Error

Abstract

The invention provides a two-vector model predictive control method for reducing steady-state tracking error, comprising: collecting the actual values ​​of inverter three-phase grid-connected voltage and three-phase grid-connected current, and using Clarke transformation to obtain The voltage value and current value; calculate the output reference voltage vector of the three-phase inverter according to the obtained voltage value and current value, and calculate the amplitude and phase angle of the output reference voltage vector; judge the output reference voltage The large sector where the vector is located and the specific interval in the large sector; determine the optimal vector combination and the duty cycle of each vector according to the shortest distance; determine the duty cycle of the basic voltage vector of each inverter; use pulse width Modulation technology to realize the control of the system. The method of the invention adds two candidate vector combinations, reduces the error between the reference voltage vector and the composite vector, and effectively improves the current steady-state tracking performance of the system.

Description

technical field [0001] The invention relates to the field of electric current conversion technology and control field of power electronics, in particular to a two-vector model predictive control method for reducing steady-state tracking error. Background technique [0002] The traditional predictive control method only has a single vector action in a control cycle, and the steady-state performance of the system is poor. A large number of studies have shown that using multiple vectors in a single sampling period can effectively improve the steady-state performance of the system. Common methods include voltage space vector modulation and two-vector predictive control. The former has better steady-state performance, but the modulation process is more complicated, the calculation amount of the system is relatively large, the requirements for the CPU are relatively high, and the requirements for the switching frequency are also high. Two-vector predictive control can effectivel...

AI Technical Summary

Problems solved by technology

This method only considers the combination of vectors in the same sector, and the output vector is a local optimal value, not a global optimal value, which is likely to cause a large current tracking error, and the system's steady-state performance is not optimal.

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