Construction method for neural network Alpha-order inverse controller of bearing-free brushless DC motor

Abstract

The invention discloses a construction method for a neural network Alpha-order inverse controller of a bearing-free brushless DC motor. Firstly, two PWM (Pulse-Width Modulation) inverters and the bearing-free brushless DC motor serve as a whole to form a compounded to-be-controlled target; an adopted static neural network and six integrators construct the neural network inverse of the compounded to-be-controlled target; then the neural network inverse is placed in front of the compounded to-be-controlled target and is connected with the compounded to-be-controlled target in series to form a pseudo linear system, and two designed position controllers and a speed controller form a linear close-loop controller; and finally, the linear close-loop controller, the neural network inverse and thetwo PWM inverters are connected in series in sequence to form the neural network Alpha-order inverse controller of the bearing-free brushless DC motor. The construction method realizes the independent control of the radial displacement and the rotational speed of the bearing-free brushless DC motor rotor, ensures the steady suspension and operation of the motor rotor, and enables the bearing-freebrushless DC motor to obtain favorable dynamic and static performance and load disturbance resistance.

Description

technical field [0001] The invention relates to a neural network α-order inverse controller for a bearingless brushless DC motor, which is suitable for high-performance control of the bearingless brushless DC motor and belongs to the technical field of electric drive control equipment. Background technique [0002] Brushless DC motor combines the characteristics of DC motor and AC motor. It has the advantages of good speed regulation performance, easy starting, load starting, long life, etc., and it is easy to maintain, low noise, and does not have a series of problems caused by brushes. . The bearingless brushless DC motor uses the magnetic field force to realize the suspension of the motor rotor, which not only has the advantages of the brushless DC motor, but also has the frictionless, wear-free, lubrication and sealing of the magnetic bearing motor, high speed, high precision, and long life. Long characteristics, with great potential engineering application value. [0...

AI Technical Summary

Problems solved by technology

However, there has not been any published literature on the design of neural network inverse decoupling controllers for bearingless brushless DC motors; due to the particularity of the structure of bearingless brushless DC motors, it is necessary to deduce the mathematics of its torque system and suspension system in sections model, and its reversibility is analyzed in sections, and its corresponding neural network inverse system structure is also different from other bearingless motors

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