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Extreme learning machine based control method for asynchronous motor drive system of electric automobile

A technology of extreme learning machine and asynchronous motor, applied in the direction of AC motor control, control system, electrical components, etc.

Active Publication Date: 2017-05-10
QINGDAO UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Traditional neural network learning algorithms (such as BP algorithm) need to artificially set a large number of network training parameters, and it is easy to generate local optimal solutions

Method used

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  • Extreme learning machine based control method for asynchronous motor drive system of electric automobile
  • Extreme learning machine based control method for asynchronous motor drive system of electric automobile
  • Extreme learning machine based control method for asynchronous motor drive system of electric automobile

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Embodiment Construction

[0109] The basic idea of ​​the present invention is: Utilize the extreme learning machine to approach the highly nonlinear function in the asynchronous motor system considering the iron loss, and combine the adaptive and backstepping technology to construct the controller, and introduce the command filtering technology into the recursive process of the Lyapunov function In the selection and construction of the intermediate virtual control signal, the control law is recursively obtained, and the corresponding adaptive law is designed to adjust the unknown parameters; the command filtering technology is introduced, and the derivative signal of the command signal can be generated without differential operation. The amount of calculation is reduced, and the problem of "computation explosion" caused by the continuous derivation of the virtual control function by the traditional backstepping method is solved. At the same time, by introducing an error compensation mechanism, the error ...

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PUM

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Abstract

The invention discloses an extreme learning machine based control method for an asynchronous motor drive system of an electric automobile. According to the invention, aiming at a problem of nonlinear and iron loss problem of a prior electric automobile motor drive system, a command filtering technology is introduced into a traditional backstepping design method. Through the introduction of a compensation mechanism, errors caused by filtering waves are reduced and a problem of calculation explosion caused by continuous derivation in traditional backstepping control is solved successfully. According to the invention, by utilizing the extreme learning machine algorithm for approximating a nonlinear function in the motor drive system, the method provided by the invention is combined with the command filtering technology and a self-adaptive backstepping method. Through regulation by utilizing the method provided by the invention, operation of the motor can reach a stable state quickly. The method is suitable for control subjects requiring quick dynamic response such as the electric automobile drive system. A simulation result shows that the control method provided by the invention can eliminate influence due to parameter uncertainty and is beneficial to ideal control effect, so that quick and stable response to rotation speed is realized.

Description

technical field [0001] The invention belongs to the technical field of speed regulation control of electric vehicle motors, and in particular relates to a control method of an electric vehicle asynchronous motor drive system based on an extreme learning machine. Background technique [0002] Since the international financial crisis, developed countries such as the United States, Europe, Japan, and South Korea have been promoting the transformation and development of the automobile industry, and another round of upsurge in the development of new energy vehicles has formed globally. Among all technological innovations, motor drives play an extremely important role, because future drive methods must have the characteristics of low energy consumption, more environmental protection, and more sustainability. [0003] Electric vehicles include mechanical systems such as motor drive and control systems, driving force transmission, and working devices to complete established tasks. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02P25/02H02P23/00
CPCH02P23/0027H02P25/02
Inventor 马玉梅于金鹏于海生赵林牛浩韩玉西
Owner QINGDAO UNIV
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