Ooussama Belkacem Djaidja, H. Mekki, Samir Zeghlache, A. Djerioui
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A new improved control for power quality enhancement in double fed induction generator using iterative learning control
This work presents a new Fault Tolerant Control approach for a doubly fed induction generator using Iterative Learning Control when the fault occurs. The goal of this research is to apply the proposed ILC controller in conjunction with vector control for doubly fed induction generator to enhance its reliability and availability under broken rotor bars. However, the performances of classical VC control are often characterized by their inability to deal with the effects of faults. To overcome these drawbacks, a combination of VC control and iterative learning control is described. The input control signal of the VC controller is gradually regulated by the ILC harmonic compensator in order to eliminate the faults effect. The improvement of this approach related to active and reactive power ripples overshoot and response time have been explained. Which active and reactive power response time have been reduced more than 84% and 87.5 % respectively. The active and reactive power overshoots have been reduced about 45% and 35% respectively. The obtained results emphasize the efficiency and the ability of the proposed FTC to enhance the power quality in faulty condition.
期刊介绍:
Diagnostyka – is a quarterly published by the Polish Society of Technical Diagnostics (PSTD). The journal “Diagnostyka” was established by the decision of the Presidium of Main Board of the Polish Society of Technical Diagnostics on August, 21st 2000 and replaced published since 1990 reference book of the PSTD named “Diagnosta”. In the years 2000-2003 there were issued annually two numbers of the journal, since 2004 “Diagnostyka” is issued as a quarterly. Research areas covered include: -theory of the technical diagnostics, -experimental diagnostic research of processes, objects and systems, -analytical, symptom and simulation models of technical objects, -algorithms, methods and devices for diagnosing, prognosis and genesis of condition of technical objects, -methods for detection, localization and identification of damages of technical objects, -artificial intelligence in diagnostics, neural nets, fuzzy systems, genetic algorithms, expert systems, -application of technical diagnostics, -diagnostic issues in mechanical and civil engineering, -medical and biological diagnostics with signal processing application, -structural health monitoring, -machines, -noise and vibration, -analysis of technical and civil systems.