Samir Zeghlache

Work place: Laboratoire d’Analyse des Signaux et Systèmes, Department of Electronics, University Mohamed Boudiaf of M’Sila, BP 166, Ichbilia 28000, Algeria

E-mail: zegsam5@gmail.com

Website:

Research Interests: Process Control System, Control Theory

Biography

Samir Zeghlache was born in Sétif, Algeria. He received his Engineer degree in Automatic from M’Sila University, Algeria, in 2006 and the Magister Diploma from Military Polytechnic School, -Bordj el Bahri- Algiers, Algeria, in 2009, all in Electrical Engineering. He received the doctorate degree in electronic from the University of M’Sila, Algeria. In 2011, he joined M’Sila University, Algeria, where he works currently as lecturer. His research interests are non linear system control. He is the author and co-author of numerous articles on the fault-tolerant control of vertical flight devices. In 2017, he created the first doctoral school in automatic in the history of the University of M'Sila.

Author Articles
Adaptive RBFNN Strategy for Fault Tolerant Control: Application to DSIM under Broken Rotor Bars Fault

By Noureddine Layadi Samir Zeghlache Ali Djerioui Hemza Mekki Fouad Berrabah

DOI: https://doi.org/10.5815/ijisa.2019.02.06, Pub. Date: 8 Feb. 2019

This paper presents a fault tolerant control (FTC) based on Radial Base Function Neural Network (RBFNN) using an adaptive control law for double star induction machine (DSIM) under broken rotor bars (BRB) fault in a squirrel-cage in order to improve its reliability and availability. The proposed FTC is designed to compensate for the default effect by maintaining acceptable performance in case of BRB. The sufficient condition for the stability of the closed-loop system in faulty operation is analyzed and verified using Lyapunov theory. To proof the performance and effectiveness of the proposed FTC, a comparative study within sliding mode control (SMC) is carried out. Obtained results show that the proposed FTC has a better robustness against the BRB fault.

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