IMPLEMENTATION OF A SIMPLE SELF-TUNED NEURO FUZZY BASED IM DRIVE
Journal Title: International Journal of Engineering Sciences & Research Technology - Year 0, Vol 4, Issue 8
Abstract
A novel simplified self-tuned neuro–fuzzy controller (NFC) for speed control of an induction motor (IM) drive is presented in this paper. The proposed NFC amalgamates fuzzy logic and a four-layer neural network structure. Only speed error is employed as input to the NFC so that the computational encumbrance of the NFC is reduced and it becomes congruous for authentic-time industrial drive applications. Predicated on the erudition of back-propagation algorithm, an unsupervised self-tuning method is developed to adjust membership functions and weights of the proposed NFC so that the performance will be kindred to that of the conventional two-input NFC. The consummate drive incorporating the proposed self-tuned NFC is experimentally implemented utilizing a digital signal-processor board DS-1104 for a laboratory 1/3-hp motor .The efficacy of the proposed NFC-predicated vector control of IM drive is tested in both simulation and experiment at different operating conditions. Comparative results show that the simplification of the proposed NFC does not decrement the system performance as compared to the conventional NFC. In order to prove the preponderating of the proposed simplified NFC, the performances of the proposed NFC are additionally compared to those obtained by a conventional proportional–integral controller.
Authors and Affiliations
G. Yuva Kishore*
Keywords
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