Fault Tolerant Control using Artificial Neural Network For Induction Motor
| dc.contributor.author | Mekhalfia, Fadhila | |
| dc.date.accessioned | 2020-10-14T13:22:37Z | |
| dc.date.available | 2020-10-14T13:22:37Z | |
| dc.date.issued | 2019-01 | |
| dc.description.abstract | In this article, a fault tolerance control based on a neural network for an induction machine is proposed, and a fault-tolerant command via backstepping control and based on an extended Kalman filter is designed. Using the residual signal generated from some calculation passing through the filter, a fault compensation loop of the neural network is introduced. This neural network is a four-layered perceptron, which attempts to minimize the error induced by the defect. In this context, a fault-tolerant control scheme is obtained. Operation characteristics of the proposed drive are compared to the fault tolerant control based on Kalman filter to verify effectiveness under various conditions by examining robustness of control in the presence of defects. Simulation results are tested in matlab / simulink environment to illustrate the proposed technique performance. | en_US |
| dc.identifier.uri | http://dspace.univ-msila.dz:8080//xmlui/handle/123456789/19903 | |
| dc.publisher | Université de M'sila | en_US |
| dc.subject | Three phases induction machine; Fault tolerant control; neural network. | en_US |
| dc.title | Fault Tolerant Control using Artificial Neural Network For Induction Motor | en_US |
| dc.type | Article | en_US |