Predication control method for brushless DC motor drive system

Abstract

The invention relates to a predication control method for a brushless DC motor drive system. According to the invention, current value of a practical system and a current value based on a hybrid logic dynamic model and subjected to state estimation are collected and compared, and future parameters are predicated according to history parameters of the system, namely, state estimation is performed on the system. Current is taken as the major control object of the design in the invention. The controller takes comparison signals of inverter output signals of the practical brushless DC motor drive system and output signals of the state estimator as reference signals. After estimation of future moment parameters of the system is performed, an optimized target function is set, so that the optimal control volume of the next moment is selected and an aim of prediction control is achieved. By adopting the method, data volume is simplified, control features of the brushless DC motor are improved, inhibition on electromagnetic torque pulse is realized and practical application is facilitated.

Description

technical field [0001] The invention relates to the technical field of a brushless DC motor drive system, in particular to a predictive control method for a brushless DC motor drive system. Background technique [0002] In the brushless DC motor drive system, the motor drive system is composed of the motor body, inverter, sensor and controller. The analysis and involvement of the motor control system are mostly based on the mathematical model of the inverter and the motor. The inverter is based on the controller The switching signal sent out modulates a voltage pulse sequence of a certain frequency and amplitude, which is a typical nonlinear link. These voltage pulses act on the inductive motor winding to generate a continuous state current. Therefore, the inverter and the motor constitute a A hybrid system driven by discrete events with continuous state evolution, the traditional predictive control method of the brushless DC motor drive system regards the power switching de...

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Problems solved by technology

[0002] In the brushless DC motor drive system, the motor drive system is composed of the motor body, inverter, sensor and controller. The analysis and involvement of the motor control system are mostly based on the mathematical model of the inverter and the motor. The inverter is based on the controller The switching signal sent out modulates a voltage pulse sequence of a certain frequency and amplitude, which is a typical nonlinear link. These voltage pulses act on the inductive motor winding to generate a continuous state current. Therefore, the inverter and the motor constitute a A hybrid system driven by discrete events with continuous state evolution, the traditional predictive control method of the brushless DC motor drive system regards the power switching device as an ideal device, and takes the average model of one output period of the system as a unit of predictive control. This method ignores the influence of the typical nonlinear link of the switching state of the power switching device in a cycle on the system output. In the prior art, a mixed logic dynamic model of the brushless DC motor drive system is described, and based on this The model performs predictive control on the DC motor drive system, which can get better control effect. However, due to the huge amount of data to be processed by this predictive control method, it is not conducive to the realization of hardware, and also limits its application in real life.

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