Command filtering control method of extreme learning machine of permanent-magnet synchronous motor for electric vehicle

Abstract

The invention discloses a command filtering control method of an extreme learning machine of a permanent-magnet synchronous motor for an electric vehicle. According to the control method, aiming at the problems of iron loss and non-linearity existing in an electric vehicle motor driving system, a command filtering technology is introduced to a traditional back-stepping design method, an error generated by filtering is reduced by introducing a compensation mechanism, and the problem of computation explosion caused by continuous derivation during the controller design process by the traditional back-stepping design method is successfully solved. An extreme learning machine algorithm approaches to a non-linearity function in the system, and the command filtering technology and a self-adaptive back-stepping method are combined; after adjustment by the control method, the operation of a motor can rapidly reach a stable state, and the control method is more suitable for a control object, such as a driving system for the electric vehicle, requiring rapid dynamic response; and a simulation result shows that the influence of parameter uncertainty can be solved with the adoption of the control method, an ideal control effect is favorably ensured, and rapid and stable response to a rotational speed is achieved.

Description

technical field [0001] The invention belongs to the technical field of speed regulation control of electric vehicle motors, and in particular relates to an extreme learning machine command filter control method for permanent magnet synchronous motors used in electric vehicles. 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 estab...

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

Images