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dc.contributor.authorHazari, Md. Rifat-
dc.contributor.authorJahan, Effat-
dc.contributor.authorMannan, Mohammad Abdul-
dc.contributor.authorTamura, Junji-
dc.date.accessioned2024-01-16T10:39:30Z-
dc.date.available2024-01-16T10:39:30Z-
dc.date.issued2015-
dc.identifier.citationMd. Rifat Hazari, Effat Jahan, Mohammad Abdul Mannan, Junji Tamura, “Design and Simulation of Artificial Neural Network (ANN) Based Speed Control for an Induction Motor Taking Core Loss and Stray Load Losses into Account”, Journal of Control & Instrumentation (STM Journals), Vol. 6, Issue 3, pp. 13-22, 2015.en_US
dc.identifier.issn2229 - 6972-
dc.identifier.urihttp://dspace.aiub.edu:8080/jspui/handle/123456789/2047-
dc.description.abstractIndirect field oriented control (FOC) scheme has been preferred due to its superior performance for induction motor (IM). Core loss (CL) and stray load losses (SLLs) are generally neglected in the mathematical model of IM. But it should be considered in the mathematical model of IM to precisely control the torque and flux. Conventional PI controller has overshooting effect at the transient period of the speed response curve. Artificial neural network (ANN) is suitable as a controller for nonlinear systems such as IM. In this paper, an ANN-based speed controller is proposed to control the speed of IM. Simulations analyses have been performed using MATLAB/SIMULINK. The results showed better performance from the proposed controller to control the speed of IM at the transient and steady-state condition without any overshooting effect as compared to the PI controller.en_US
dc.language.isoenen_US
dc.publisherSTM Journals, an imprint of CELNET (Consortium e-Learning Network Pvt. Ltd.)en_US
dc.subjectInduction motoren_US
dc.subjectfield oriented controlen_US
dc.subjectartificial neural network controlleren_US
dc.subjectcore lossen_US
dc.subjectstray load lossen_US
dc.titleDesign and Simulation of Artificial Neural Network (ANN) Based Speed Control for an Induction Motor Taking Core Loss and Stray Load Losses into Accounten_US
dc.typeArticleen_US
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