ADALINE approach for induction motor mechanical parameters identification

Hamid Sediki (1) , Ali Bechouche (1) , Djaffar Ould Abdeslam (2) , Salah Haddad (1)

1 Department of Electrical Engineering
2 MIPS - Modélisation, Intelligence, Processus et Système

Two new methods to identify the mechanical parameters in induction motor based field oriented drives are presented in this paper. The identified parameters are: the moment of inertia and the viscous damping coefficient. The proposed methods are based on the adaptive linear neuron (ADALINE) networks. The two parameters are derived and optimized during the online training process. During the identification phase, the motor torque is controlled by the well-known field oriented control strategy. This torque is subjected to variations in order to obtain mechanical speed transients. The two proposed methods are simple to implement compared to the previous techniques. They require only the stator current and mechanical speed measurements. Finally, the effectiveness of the two methods and the accuracy of the derived parameters are proven experimentally by two direct starting tests. The originality of this work is the building of a model representation that it is suitable for implementation with ADALINE networks. This leads to a simple implementation and ease of mechanical parameters identification.

Mots clés: Adaptive linear neuron; Artificial neural networks; Field oriented control; Induction motor; Parameters identification

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Hamid Sediki, Ali Bechouche, Djaffar Ould Abdeslam, Salah Haddad. ADALINE approach for induction motor mechanical parameters identification. Mathematics and Computers in Simulation, 2013, 90 (-), pp.86-97. ⟨10.1016/j.matcom.2012.05.003⟩. ⟨hal-00985414⟩