DocumentCode :
2579323
Title :
Robust DTC-SVM method for matrix converter drives with model reference adaptive control scheme
Author :
Sim, Gyung-Hun ; Lee, Kyo-Beum ; Huh, Sung-Hoi ; Blaabjerg, Frede
Author_Institution :
Chonbuk Nat. Univ., Jeonju
fYear :
2007
fDate :
2-5 Sept. 2007
Firstpage :
1
Lastpage :
8
Abstract :
This paper presents a new robust DTC-SVM control system for high performance induction motor drives fed by a matrix converter with variable structure - model reference adaptive control scheme (VS-MRAC). It is possible to combine the advantages of matrix converters with the advantages of the DTC strategy using space vector modulations and a deadbeat algorithm in the stator flux reference frame. The lumped disturbances such as parameter variation and load disturbance of the system are estimated by a neuro-sliding mode approach based on model reference adaptive control (MRAC). An adaptive observer is also employed to bring better responses at the low speed operation. Simulation results are shown to illustrate the performance of the proposed system.
Keywords :
adaptive control; induction motor drives; machine control; matrix convertors; robust control; support vector machines; torque control; variable structure systems; adaptive observer; direct torque control; induction motor drive; matrix converter drive; model reference adaptive control scheme; neuro-sliding mode; robust DTC-SVM method; robust control; variable structure; Adaptive control; Control system synthesis; Induction motor drives; Matrix converters; Pulse width modulation inverters; Reactive power; Robust control; Stators; Virtual colonoscopy; Voltage control; DTC-SVM; VS-MRAC(Variable Structure - Model Reference Adaptive Control); matrix converter drive, robust control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Electronics and Applications, 2007 European Conference on
Conference_Location :
Aalborg
Print_ISBN :
978-92-75815-10-8
Electronic_ISBN :
978-92-75815-10-8
Type :
conf
DOI :
10.1109/EPE.2007.4417256
Filename :
4417256
Link To Document :
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