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Neural network-based ultra-high-speed permanent magnet synchronous motor speed observation method

A neural network and speed technology, which is applied in the control of generators, motor generators, electronic commutation motor control, etc., can solve the problems of measurement noise sensitivity, achieve strong robustness and adaptability, and improve speed control. performance effect

Active Publication Date: 2018-02-09
NANJING UNIV OF SCI & TECH
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Problems solved by technology

Methods such as direct calculation, model reference adaptation, and observer all rely on the nonlinear mathematical model and internal parameters of PMSM. These methods have the problem of self-adaptation to motor parameters and load disturbances and sensitivity to measurement noise.

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  • Neural network-based ultra-high-speed permanent magnet synchronous motor speed observation method
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  • Neural network-based ultra-high-speed permanent magnet synchronous motor speed observation method

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Embodiment Construction

[0036] combine figure 1 , the sensorless ultra-high speed permanent magnet synchronous motor speed estimation method based on neural network of the present invention, comprises the following steps:

[0037] Step 1. Detect the motor bus terminal and read the three-phase current i at time k a (k), i b (k), i c (k), three-phase voltage u a (k), u b (k), u c (k), after Clark (3s / 2s) transformation, the current i in the α-β two-phase stationary coordinate system at time k is obtained α (k),i β (k), and voltage u α (k), u β (k).

[0038] Step 2. Calculate the current i in the α-β two-phase stationary coordinate system at time k α (k),i β (k), voltage u α (k), u β (k) and estimated value of rotor speed at time k-1 and rotor angle estimates As an input, it is sent to the three-layer dynamic recursive neural network rotor speed estimation module to estimate the rotor speed at k time, and obtain the one-step estimated value of the rotor speed at k time

[0039] Among...

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Abstract

The invention relates to a neural network-based ultra-high-speed permanent magnet synchronous motor speed observation method. According to the method of the invention, a speed estimation equation is discretized; the discrete linear equation is substituted into a three-layer dynamic recurrent neural network to calculate a rotation speed estimated value and a rotor angle estimated value; the rotor angle estimated value is corrected through current estimation error; and the rotor angle estimated value is further substituted into the dynamic recurrent neural network for operation; and the rotationspeed of an ultra-high-speed permanent magnet synchronous motor can be estimated in real time in the dynamic operation process of the ultra-high-speed permanent magnet synchronous motor. With the method of the invention adopted, sensorless rotation speed observation is realized, and the rotation speed control precision of the motor is improved.

Description

technical field [0001] The invention belongs to the technical field of motor control, and in particular relates to a sensorless motor speed observation method based on a neural network. Background technique [0002] The wide application of ultra-high-speed permanent magnet motors in modern society has attracted many scholars and institutions at home and abroad to study them. Ultra-high-speed permanent magnet synchronous motor (PMSM) has the advantages of small size, light weight, high power density, high reliability, and good dynamic response performance. Therefore, in the fields of industrial manufacturing, medical treatment, energy, ships and national defense, ultra-high-speed PMSM applications The prospect is very broad, for example, it can be applied to industrial ultra-high-speed milling processing technology, medical ultra-high-speed centrifuge, centrifugal air compressor, etc. [0003] In the control system of ultra-high-speed PMSM, speed detection is essential. How...

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Application Information

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IPC IPC(8): H02P21/13H02P21/18H02P21/00
CPCH02P21/0014H02P21/0085H02P21/13H02P21/18
Inventor 郭健洪宇吴益飞薛舒严钱抒婷沈宏丽周梦兰林立斌黄迪王天野
Owner NANJING UNIV OF SCI & TECH