Control Method of Bearingless Permanent Magnet Motor Suspension System Based on Double Inverter Model

Abstract

The invention discloses a bearingless permanent magnet motor suspension system control method based on dual inverse models. An inverse model base is formed by a normal inverse model and a fault inverse model of a complex controlled object; an inverse model in the inverse model base is selected as the inverse model of the complex controlled object, parameters and weight coefficients of a corresponding neural network are adjusted and determined to make the inverse model base realize the inverse system function of the complex controlled object, the inverse model base is serially connected in front of the complex controlled object to form a pseudo-linear system, and the pseudo-linear system is decoupled into two single-input single-output displacement second-order integral sub-systems; additional controllers are designed for the two displacement second-order integral sub-systems separately to form a linear closed-loop controller; and a neural network inverse fault-tolerant controller is formed by the linear closed-loop controller, the inverse model base, a 2 / 3 current converter and a current tracking type inverter collectively to perform fault-tolerant control on a bearingless permanent magnet motor suspension system, so that the decoupling control of an original system between radial positions in normal or fault operating conditions can be realized.

Description

technical field [0001] The invention is a control method for a bearingless permanent magnet motor suspension system based on a dual neural network inverse model, which is suitable for high-performance control of the bearingless permanent magnet motor suspension system and belongs to the technical field of special electric drive control equipment. Background technique [0002] Bearingless permanent magnet motor integrates the functions of traditional permanent magnet motor and magnetic suspension bearing. It has the advantages of no friction and wear, no lubrication, high speed and high precision, long life, high power density, and high efficiency. It is used in semiconductor manufacturing, biomedicine, and flywheels. Energy storage, precision numerical control machine tools, aerospace and other special fields have been more and more widely used. However, these special fields have higher and stricter requirements for the continuous operation of bearingless permanent magnet mo...

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Problems solved by technology

However, the use of neural network inverse system method to realize the fault-tolerant control of bearingless permanent magnet motor suspension system has not been reported in the literature.

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