Method for identifying resistance parameters of rotors of induction motor on basis of Elman neural network

A technology of neural network and rotor resistance, applied in neural learning methods, biological neural network models, measuring resistance/reactance/impedance, etc.

Inactive Publication Date: 2013-02-20
HENAN UNIV OF SCI & TECH
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Problems solved by technology

[0003] In order to solve the above-mentioned technical problems, the present invention proposes an induction motor rotor resistance parameter identification method based on the Elman neural network based on the MRAS scheme of the flux linkage model, so as to solve the problem of obtaining the reference model when the speed adjustment signals are different, and Requirements for the speed sensor in the identification of the rotor resistance parameters of the asynchronous motor

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  • Method for identifying resistance parameters of rotors of induction motor on basis of Elman neural network
  • Method for identifying resistance parameters of rotors of induction motor on basis of Elman neural network
  • Method for identifying resistance parameters of rotors of induction motor on basis of Elman neural network

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[0035] The third step is to obtain training samples. Take the above input signal as the main control condition, combine it with other input variables (such as the change of slip frequency), and use the BP offline algorithm to train to obtain a batch of training samples, and then use these data as a reference to establish a rotor resistance model, using this model The output of the network is used as the target value of the network to carry out error backpropagation and weight correction. The specific implementation is as follows:

[0036] a) Establish a BP network with the input parameters and output parameters in step 3, such as Figure 5 , the input vector is , the hidden layer output vector: , the output layer output vector: , expecting an output vector: , the weight matrix between the input layer and the hidden layer is denoted by V, , where the column vector is the weight vector corresponding to the jth neuron in the hidden layer, and the weight matrix betwee...

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Abstract

Disclosed is a method for identifying resistance parameters of rotors of induction motors on the basis of an Elman neural network. The method has the advantages that the Elman neural network and a network structure are determined, a training sample is processed, and the parameters are identified, so that a reference model can be obtained when speed regulating signals are different, and requirements of identification for the resistance parameters of the rotors of the asynchronous motors on rotational speed sensors are met.

Description

technical field [0001] The invention belongs to the field of asynchronous motors and relates to a high-performance variable frequency speed regulation system parameter identification method. Background technique [0002] When the motor is running, its parameters will change due to the influence of internal and external conditions. The temperature rise and frequency of the motor will affect the rotor resistance, which can vary by up to 50% with the temperature of the motor. When the frequency of the rotor current is high, the skin effect can cause the rotor resistance to change several times. The change will cause the change of the time constant of the rotor of the motor, etc., resulting in the distortion of various motor feedback signals calculated based on the fixed parameter settings. Based on such feedback, the motor field orientation coordinates often deviate from the actual, resulting in large speed, torque deviation or pulsation, and the performance of the control sys...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R27/02G06N3/08
Inventor 范波李兴谢冬冬史光辉
Owner HENAN UNIV OF SCI & TECH
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