ANN-inversion based fractional order QFT robust control for PMSM

Author

Qinghong Xu ; Jiacai Huang ; Hongsheng Li ; Lei Zhou

Author_Institution

Sch. of Autom., Nanjing Inst. of Technol., Nanjing, China

fYear

2014

fDate

28-30 July 2014

Firstpage

2396

Lastpage

2399

Abstract

To improve the performance of the PMSM, an ANN-Inversion based fractional order QFT(FOQFT) robust control scheme for the PMSM is proposed. Firstly, a BP neural network is used to approximate the inverse system of PMSM, and the composite pseudo-linear system, consisted of the ANN-Inversion system and the controlled PMSM system, is equivalent to a linear system with disturbance. Then, a FOQFT control scheme is proposed based on the QFT method and fractional calculus, and the parameters of the FOQFT controller are optimized by Particle Swarm Optimization (PSO) algorithm. Finally, case study is conducted on a PMSM system and results show the effectiveness of the proposed control scheme.

Keywords

backpropagation; linear systems; machine control; neurocontrollers; particle swarm optimisation; permanent magnet generators; robust control; synchronous generators; ANN-inversion based fractional order QFT robust control; BP neural network; FOQFT robust control scheme; PMSM system; PSO algorithm; artificial neural networks; composite pseudolinear system; fractional calculus; inverse system; linear system; particle swarm optimization algorithm; permanent magnet synchronous generator; Approximation methods; Control systems; Mathematical model; Neural networks; Particle swarm optimization; Robust control; Rotors; ANN-Inversion; Fractional Caculus; PMSM; Particle Swarm Optimization; QFT;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (CCC), 2014 33rd Chinese

Conference_Location

Nanjing

Type

conf

DOI

10.1109/ChiCC.2014.6897009

Filename

6897009