| Fractional order complementary non-singular terminal sliding mode control of PMSM based on neural network
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| Jinliang Zhang 1, Dunbin Zhu 1, Wei Jian 1, Wentao Hu 1, Guosheng Peng 1, Yufeng Chen 1, Zhihu Wang 2 |
1School of Electrical and Information Engineering , Hubei University of Automotive Technology
2Dongfeng Automobile Power Parts Co. Ltd |
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| ABSTRACT |
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Aiming at the sensitivity problems of uncertain factors such as parameter variation, external disturbance and friction for the
permanent magnet synchronous motor control system of electric vehicle, a fractional order complementary non-singular terminal
sliding mode control method based on neural network is proposed. The mathematical model of permanent magnet synchronous
motor with uncertain factors was established. The sliding mode controller was designed by combining the generalized sliding
mode surface and the complementary sliding mode surface, which shortened the arrival time from the state trajectory to sliding
mode surface. The fractional calculus operator with fi ltering characteristics was used to improve the position tracking accuracy
and reduce the chattering. As for the variety of uncertain disturbances, the neural network was used to estimate the system total
uncertainty and compensate online to further improve the dynamic response ability and anti-interference ability. Finally, the
simulation results verify the eff ectiveness and feasibility of the proposed method, which can provide theoretical and technical
support for improving the control accuracy of permanent magnet synchronous motor and the development of electric vehicles. |
| Key Words:
Permanent magnet synchronous motor · Fractional order complementary · Neural network · Electric vehicle drive system · Non-singular terminal sliding mode
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Corresponding Author.
Jinliang Zhang , Email. 
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