Decoupling controller for suspension force subsystem of five-degree-of-freedom bearingless permanent magnet synchronous motor

Abstract

The invention discloses a decoupling controller of a suspension force subsystem of a five-degree-of-freedom bearingless permanent magnet synchronous motor. The composite controlled objects are connected in series with an online neural network inverse module of the suspension force subsystem and an additional controller module, and the additional controller is connected in series. The module consists of five sliding mode controllers, the input of each sliding mode controller is an error value between a given displacement and a corresponding real-time displacement; the online neural network inverse module of the suspension force subsystem is composed of a neural network system, online learning Algorithm module and 10 integrators S ‑1 composition, each displacement control amount and each displacement control amount are passed through an integrator S ‑1 The single integral obtained after and each displacement control quantity are connected by two integrator S in series ‑1 The double integrals obtained after are input to the neural network system; the input of the online learning algorithm module is the double integral of the five displacement control variables and the corresponding five errors of the real-time displacement, and the output is the adjusted weight matrix to improve the suspension. Control performance.

Description

technical field [0001] The invention relates to a five-degree-of-freedom bearingless permanent magnet synchronous motor, specifically a sliding mode decoupling controller for a suspension force subsystem of a five-degree-of-freedom bearingless permanent magnet synchronous motor based on an online neural network inverse, and belongs to the technical field of electric drive control equipment. Background technique [0002] The bearingless permanent magnet synchronous motor integrates the advantages of magnetic suspension bearings without lubrication, no mechanical wear, low noise and long service life, and at the same time has the excellent operating characteristics of permanent magnet synchronous motors. The bearingless permanent magnet synchronous motor has the advantages of low loss, high efficiency, no excitation current, simple control loop, high power factor, high speed, high precision, etc. It has broad application prospects in aerospace, biomedicine, semiconductor manufa...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to overcome the deficiencies in the decoupling control method of the existing five-degree-of-freedom bearingless permanent magnet synchronous motor suspension force subsystem, and propose a five-degree-of-freedom bearingless permanent magnet synchronous motor suspension based on an online neural network inverse The force subsystem sliding mode decoupling controller adjusts the connection weights of the neural network online through the design algorithm, so that the accuracy of the inverse model of the five-degree-of-freedom bearingless permanent magnet synchronous motor suspension force subsystem is improved, and the pseudo Linear second order radial displacement x a ,y a , x b ,y b and pseudolinear second-order axial displacement z b The subsystem design sliding mode controller (Sliding Model Controller, SMC), effectively realizes the decoupling control between the suspension force of the five-degree-of-freedom bearingless permanent magnet synchronous motor, obtains good dynamic and static characteristics, and overcomes the five-degree-of-freedom bearingless The perturbation of the suspension force subsystem parameters of the permanent magnet synchronous motor, the problem of control performance degradation caused by modeling errors and load changes

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