Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Five degrees of freedom bearingless permanent magnet synchronous motor fuzzy neural network decoupling controller

A technology of fuzzy neural network and permanent magnet synchronous motor, which is applied in the field of decoupling controller to achieve the effect of fast response speed, good dynamic performance, and simple and easy-to-understand principle.

Active Publication Date: 2019-08-02
东台城东科技创业园管理有限公司
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problems existing in the control technology of the existing five-degree-of-freedom bearingless permanent magnet synchronous motor, and propose a kind of fuzzy neural network decoupling controller, combining the advantages of fuzzy logic control, neural network control and predictive control, It can simply and reliably realize the decoupling control among rotor radial levitation force, electromagnetic torque, magnetic bearing radial levitation force and axial levitation force of five-degree-of-freedom bearingless permanent magnet synchronous motor

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Five degrees of freedom bearingless permanent magnet synchronous motor fuzzy neural network decoupling controller
  • Five degrees of freedom bearingless permanent magnet synchronous motor fuzzy neural network decoupling controller
  • Five degrees of freedom bearingless permanent magnet synchronous motor fuzzy neural network decoupling controller

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0020] Such as figure 1 As shown, the fuzzy neural network decoupling controller 17 of the present invention is composed of two dynamic prediction modules 4, 5 and a fuzzy neural network system 3 connected in series, and the output ends of the two dynamic prediction modules 4, 5 are connected in series with the fuzzy neural network system The input end of 3 and the output end of the fuzzy neural network system 3 are connected to the compound controlled object 2 including the five-degree-of-freedom bearingless permanent magnet synchronous motor.

[0021] The output of compound controlled object 2 is the four radial displacements {x a ,y a ,x b ,y b}, an axial displacement z a and a rotational speed ω. The input of the first dynamic prediction module 4 is the radial displacement {x a ,y a}, axial displacement z a , Radial displacement given value and axial displacement given value The output of the first dynamic prediction module 4 is the composite control signal j ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The present invention discloses a five-degree-of-freedom bearingless permanent magnet synchronous motor fuzzy neural network decoupling controller. The controller is formed by connection in series of output ends of two dynamic prediction modules with the input end of a fuzzy neural network system, the input of a first dynamic prediction module is a radial displacement {xa, ya}, an axial displacement za and a radial displacement set value (img file='DDA0001335767690000011. TIF' wi='154' he='65' / ) and an axial displacement set value (img file='DDA0001335767690000012. TIF' wi='79' he='64' / ), and the output of the first dynamic prediction module is composite control signals ja; and the input of the second dynamic prediction module is a radial displacement {xb, yb}, a rotation speed [Omega], a radial displacement set value (img file='DDA0001335767690000013. TIF' wi='150' he='65' / ) and a rotation speed set value [Omega]*, and the output of the second dynamic prediction module is composite control signals jb and rotation speed control signals [Omega]c. The five-degree-of-freedom bearingless permanent magnet synchronous motor fuzzy neural network decoupling controller combines the fuzzy logic control to have low sample requirement, and the neural network has good dynamic performances for the system learning capacity and prediction control, and various good static dynamic performances such as rotor radial position and motor speed control can be obtained, etc.

Description

technical field [0001] The invention relates to a bearingless permanent magnet synchronous motor in the field of electric drive control equipment, specifically a decoupling controller for a bearingless permanent magnet synchronous motor based on a fuzzy neural network, which is suitable for nonlinear and multivariable five-degree-of-freedom bearingless permanent High-speed and high-precision control of magnetic synchronous motor. Background technique [0002] Permanent magnet synchronous motors are not only simple in structure, small in size, low in cost, and reliable in operation, but also have the advantages of high efficiency, high power factor, fast response, and wide speed range. They are very suitable for high-speed and high-precision industrial fields. The bearingless permanent magnet synchronous motor is a combination of bearingless technology and magnetic bearing technology with the permanent magnet synchronous motor, that is, by adding an additional set of suspensi...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): H02P21/00
CPCH02P21/001H02P21/0014
Inventor 朱熀秋杜伟吴熙潘伟孙玉坤杨泽斌
Owner 东台城东科技创业园管理有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products