Publications

2018
Saidi A, Youb L, Naceri F, Belkacem S. A Fuzzy Adaptive Control of Doubly Fed Induction Machine (DFIM). 3rd International Conference on Measurement Instrumentation and Electronics (ICMIE 2018) [Internet]. 2018. Publisher's VersionAbstract

In this paper, we are interested in the adaptive fuzzy control a technique has been studied and applied, namely adaptive fuzzy control based on theory of Lyapunov. The system based on the stability theory is used to approximate the gains Ke and kdce to ensure the stability of the control in real time .the simulations results obtained by using Matlab environment gives that the fuzzy adaptive control more robust, also it has superior dynamics performances. The results and test of robustness will be presented.

Saidi A, Youb L, Naceri F, Belkacem S. A Fuzzy Adaptive Control of Doubly Fed Induction Machine (DFIM). MATEC Web of Conferences. 2018;208 :03008.
Saidi A, Youb L, Naceri F, Belkacem S. A Fuzzy Adaptive Control of Doubly Fed Induction Machine (DFIM). 3rd International Conference on Measurement Instrumentation and Electronics (ICMIE 2018) [Internet]. 2018. Publisher's VersionAbstract

In this paper, we are interested in the adaptive fuzzy control a technique has been studied and applied, namely adaptive fuzzy control based on theory of Lyapunov. The system based on the stability theory is used to approximate the gains Ke and kdce to ensure the stability of the control in real time .the simulations results obtained by using Matlab environment gives that the fuzzy adaptive control more robust, also it has superior dynamics performances. The results and test of robustness will be presented.

Saidi A, Youb L, Naceri F, Belkacem S. A Fuzzy Adaptive Control of Doubly Fed Induction Machine (DFIM). MATEC Web of Conferences. 2018;208 :03008.
Saidi A, Youb L, Naceri F, Belkacem S. A Fuzzy Adaptive Control of Doubly Fed Induction Machine (DFIM). 3rd International Conference on Measurement Instrumentation and Electronics (ICMIE 2018) [Internet]. 2018. Publisher's VersionAbstract

In this paper, we are interested in the adaptive fuzzy control a technique has been studied and applied, namely adaptive fuzzy control based on theory of Lyapunov. The system based on the stability theory is used to approximate the gains Ke and kdce to ensure the stability of the control in real time .the simulations results obtained by using Matlab environment gives that the fuzzy adaptive control more robust, also it has superior dynamics performances. The results and test of robustness will be presented.

Saidi A, Youb L, Naceri F, Belkacem S. A Fuzzy Adaptive Control of Doubly Fed Induction Machine (DFIM). MATEC Web of Conferences. 2018;208 :03008.
Saidi A, Youb L, Naceri F, Belkacem S. A Fuzzy Adaptive Control of Doubly Fed Induction Machine (DFIM). 3rd International Conference on Measurement Instrumentation and Electronics (ICMIE 2018) [Internet]. 2018. Publisher's VersionAbstract

In this paper, we are interested in the adaptive fuzzy control a technique has been studied and applied, namely adaptive fuzzy control based on theory of Lyapunov. The system based on the stability theory is used to approximate the gains Ke and kdce to ensure the stability of the control in real time .the simulations results obtained by using Matlab environment gives that the fuzzy adaptive control more robust, also it has superior dynamics performances. The results and test of robustness will be presented.

Saidi A, Youb L, Naceri F, Belkacem S. A Fuzzy Adaptive Control of Doubly Fed Induction Machine (DFIM). MATEC Web of Conferences. 2018;208 :03008.
Benmessaoud F, Chikhi A, Belkacem S. Fuzzy Compensator of the Stator Resistance Variation of the DTC Driven Induction Motor Using Space Vector Modulation. International Conference on Advanced Intelligent Systems and Informatics. 2018 :89-97.
Benmessaoud F, Chikhi A, Belkacem S. Fuzzy Compensator of the Stator Resistance Variation of the DTC Driven Induction Motor Using Space Vector Modulation. In: Advances in Intelligent Systems and Computing. Vol. 845. © Springer Nature Switzerland AG 2019, ISBN: 978-3-319-99009-5 ; 2018.
Benmessaoud F, Chikhi A, Belkacem S. Fuzzy Compensator of the Stator Resistance Variation of the DTC Driven Induction Motor Using Space Vector Modulation. International Conference on Advanced Intelligent Systems and Informatics. 2018 :89-97.
Benmessaoud F, Chikhi A, Belkacem S. Fuzzy Compensator of the Stator Resistance Variation of the DTC Driven Induction Motor Using Space Vector Modulation. International Conference on Advanced Intelligent Systems and Informatics AISI 2018 [Internet]. 2018. Publisher's VersionAbstract

This paper presents the contribution of a fuzzy controller to compensate the influence of stator resistance variation which can degrade the performance and stability of a direct torque control (DTC). Nevertheless, the original term DTC refers to a strategy that provides good performance, but it also has some negative aspects to the level of switching and inaccuracy in the engine model which recommends the use of a new technique the SVM which proposes an algorithm based on the modulation of the space vector in order to carry out a predictive regulation of the torque and flux of the induction motor and provides a fixed switching frequency, thus improving the dynamic response and the static behavior of the DTC.

Benmessaoud F, Chikhi A, Belkacem S. Fuzzy Compensator of the Stator Resistance Variation of the DTC Driven Induction Motor Using Space Vector Modulation. International Conference on Advanced Intelligent Systems and Informatics. 2018 :89-97.
Benmessaoud F, Chikhi A, Belkacem S. Fuzzy Compensator of the Stator Resistance Variation of the DTC Driven Induction Motor Using Space Vector Modulation. International Conference on Advanced Intelligent Systems and Informatics AISI 2018 [Internet]. 2018. Publisher's VersionAbstract

This paper presents the contribution of a fuzzy controller to compensate the influence of stator resistance variation which can degrade the performance and stability of a direct torque control (DTC). Nevertheless, the original term DTC refers to a strategy that provides good performance, but it also has some negative aspects to the level of switching and inaccuracy in the engine model which recommends the use of a new technique the SVM which proposes an algorithm based on the modulation of the space vector in order to carry out a predictive regulation of the torque and flux of the induction motor and provides a fixed switching frequency, thus improving the dynamic response and the static behavior of the DTC.

Benmessaoud F, Chikhi A, Belkacem S. Fuzzy Compensator of the Stator Resistance Variation of the DTC Driven Induction Motor Using Space Vector Modulation. In: Advances in Intelligent Systems and Computing. Vol. 845. © Springer Nature Switzerland AG 2019, ISBN: 978-3-319-99009-5 ; 2018.
Benmessaoud F, Chikhi A, Belkacem S. Fuzzy Compensator of the Stator Resistance Variation of the DTC Driven Induction Motor Using Space Vector Modulation. International Conference on Advanced Intelligent Systems and Informatics AISI 2018 [Internet]. 2018. Publisher's VersionAbstract

This paper presents the contribution of a fuzzy controller to compensate the influence of stator resistance variation which can degrade the performance and stability of a direct torque control (DTC). Nevertheless, the original term DTC refers to a strategy that provides good performance, but it also has some negative aspects to the level of switching and inaccuracy in the engine model which recommends the use of a new technique the SVM which proposes an algorithm based on the modulation of the space vector in order to carry out a predictive regulation of the torque and flux of the induction motor and provides a fixed switching frequency, thus improving the dynamic response and the static behavior of the DTC.

Benmessaoud F, Chikhi A, Belkacem S. Fuzzy Compensator of the Stator Resistance Variation of the DTC Driven Induction Motor Using Space Vector Modulation. In: Advances in Intelligent Systems and Computing. Vol. 845. © Springer Nature Switzerland AG 2019, ISBN: 978-3-319-99009-5 ; 2018.
Mazouz F, Belkacem S, Ouchen S, Harbouche Y, Abdessemed R. Fuzzy control of a wind system based on the DFIG. In: Artificial Intelligence in Renewable Energetic Systems. Vol. 35. © Springer International Publishing AG 2018, ISBN: 978-3-319-73191-9 ; 2018.
Mazouz F, Belkacem S, Ouchen S, Harbouche Y, Abdessemed R. Fuzzy control of a wind system based on the DFIG. In: Artificial Intelligence in Renewable Energetic Systems. Vol. 35. © Springer International Publishing AG 2018, ISBN: 978-3-319-73191-9 ; 2018.
Mazouz F, Belkacem S, Ouchen S, Harbouche Y, Abdessemed R. Fuzzy control of a wind system based on the DFIG. In: Artificial Intelligence in Renewable Energetic Systems. Vol. 35. © Springer International Publishing AG 2018, ISBN: 978-3-319-73191-9 ; 2018.

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