Direct Torque Control Based on Space Vector Modulation with Adaptive Neural Integrator for Stator Flux Estimation in Induction Motors

Author

Zang, Chunhua ; Cao, Xianqing

Author_Institution

Coll. of Inf. Eng., Shenyang Inst. of Chem. Technol., Shenyang, China

Volume

6

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

355

Lastpage

359

Abstract

Direct torque control based on space vector modulation (SVM-DTC) preserve DTC transient merits, furthermore, produce better quality steady-state performance in a wide speed range. A new adaptive neural integration algorithm for estimating stator flux is introduced. The simulations of conventional DTC and the proposed control topologies are given and discussed. It is concluded that the proposed control topology outperforms the conventional DTC in reducing torque ripple and eliminating bad effect of dc-offset.

Keywords

induction motors; machine control; torque control; adaptive neural integrator; control topologies; direct torque control; induction motors; space vector modulation; stator flux estimation; Adaptive control; Induction motors; Programmable control; Space technology; Stators; Steady-state; Support vector machines; Topology; Torque control; Voltage control; DTC; adaptive neural integrator; space vector modulation; stator flux estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2009. ICNC '09. Fifth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3736-8

Type

conf

DOI

10.1109/ICNC.2009.356

Filename

5366435