A permanent magnet synchronous motor control system and its predictive control method

Abstract

The invention discloses a permanent magnet synchronous motor control system, comprising a space vector pulse width modulator, a three-phase bridge inverter module, a permanent magnet synchronous motor and a signal acquisition module for collecting feedback signals, characterized in that the signal acquisition The module collects the motor rotor angular velocity, rotor position angle, three-phase current at the motor input side, the DC bus voltage of the inverter module, and the duty cycle of the output of the space vector pulse width modulator; the control system also includes a function for predicting the space vector pulse width modulation The composite multi-level regulation module of the output duty ratio of the converter; the composite multi-level regulation module includes a prediction module, a prediction compensation module, a prediction correction module, and a first-level regulation module, a second-level regulation module, and a third-level regulation module connected in sequence. The invention also discloses a predictive control method of the permanent magnet synchronous motor. The invention improves the dynamic and steady state performance of the system at high speed and low control frequency, and at the same time has strong parameter robustness, and the steady state has no static difference and oscillation.

Description

technical field [0001] The invention relates to the field of permanent magnet synchronous motor control, in particular to a permanent magnet synchronous motor control system and a predictive control method thereof. Background technique [0002] At present, Model Predictive Control (MPC) is widely used in industrial process control (such as chemical and petroleum industries) due to its advantages of realizing nonlinear system control, considering complex constraints and simple design. In the permanent magnet synchronous motor drive system, the algorithm uses the precise mathematical model of the motor to predict the state solution under the action of different control variables, and selects the optimal control variable that should act in the next control cycle, so as to realize the current energy of the motor. Accurately follow the command current value. Model predictive control can make the motor current obtain good dynamic and steady-state response, but there are certain p...

AI Technical Summary

Problems solved by technology

In the actual system, these parameters will change with the working state of the motor, and there are unmodeled disturbances in the system

At high speed and low control frequency, the established discrete model is inaccurate and the motor parameter deviation is large, which will deteriorate the dynamic stability performance of the system, affect the stability of the entire system, and even damage the system in severe cases.

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