Bearing-free asynchronous motor control method based on neural network inverse system theory

Abstract

The invention discloses a bearing-free asynchronous motor control method based on a neural network inverse system theory. A composite controlled object is composed of two sets of Park inverse transformation, two sets of Clark inverse transformation, two sets of current regulating inverters, a flux linkage observer, and a bearing-free asynchronous motor; a fuzzy neural network and integrators form a fuzzy neural network inverse system; and the fuzzy neural network inverse system is in series connection with the composite controlled object; besides, the bearing-free asynchronous motor is decoupled into a pseudo linear system comprising two displacement subsystems, a rotating speed subsystem and a rotor flux linkage subsystem; and the obtained pseudo linear system is introduced into internal model control to form closed-loop control. According to the invention, the control precision is high and there is high robustness on an external disturbance, a parameter change and a modeling error, thereby realizing high-performance control on a bearing-free asynchronous motor.

Description

technical field [0001] The invention belongs to the technical field of electric drive control equipment, in particular to a bearingless asynchronous motor control method based on neural network inverse system theory. Background technique [0002] The bearingless asynchronous motor is a nonlinear, multi-variable, and strongly coupled system. Realizing the dynamic decoupling control between its electromagnetic torque and radial levitation force is the key to the stable levitation and rotation of the motor. [0003] At present, the control methods of bearingless asynchronous motors mainly include vector control and feedback linearization control. Among them, the vector control strategy based on the torque winding air-gap magnetic field orientation can realize the separate control of the torque and air-gap flux linkage of the bearingless asynchronous motor, but because the air-gap flux is still related to the torque current, it has not realized the real Decoupling control i...

AI Technical Summary

Problems solved by technology

As a complex nonlinear object, the rotor parameters of the bearingless asynchronous motor change significantly with the working conditions, coupled with the existence of load disturbance and the influence of magnetic saturation, it is very difficult to accurately model the system, so the analytical inverse system method Difficult to apply in practice

Images