Decoupling control of a five-phase fault-tolerant permanent magnet motor by radial basis function neural network inverse | Zendy

Qian Chen | Zendy; Guohai Liu | Zendy; Dezhi Xu | Zendy; Liang Xu | Zendy; Gaohong Xu | Zendy; Nazir Aamir | Zendy

Open Access

Decoupling control of a five-phase fault-tolerant permanent magnet motor by radial basis function neural network inverse

Author(s) -

Qian Chen,

Guohai Liu,

Dezhi Xu,

Liang Xu,

Gaohong Xu,

Nazir Aamir

Publication year - 2018

Publication title -

aip advances

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.421

H-Index - 58

ISSN - 2158-3226

DOI - 10.1063/1.5005841

Subject(s) - control theory (sociology) , radial basis function , decoupling (probability) , robustness (evolution) , torque , artificial neural network , computer science , internal model , machine control , control system , fault tolerance , inverse , control engineering , engineering , physics , mathematics , artificial intelligence , control (management) , distributed computing , biochemistry , chemistry , geometry , electrical engineering , gene , thermodynamics

Permanent magnet (PM) motors are employed into electric vehicles extensively because of high efficiency, high power density, and high torque density.

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