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RISS 인기검색어
- 검색키워드
- 저자 : Geetha E.K (검색결과 2 건)
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ROBUST SPEED SENSORLESS INDUCTION MOTOR DRIVES
Geetha E.K,T.Thyagarajan,Vedam Subrahmanyam 전력전자학회 2007 ICPE(ISPE)논문집 Vol.- No.-
Induction motors are widely used in industry due to the fact that they are relatively cheap, rugged and maintenance free. As a consequence, much attention has been given to the motor torque and speed control. The control schemes available today require information regarding speed of the motor, which can either be obtained by using speed sensors or without speed sensors. Speed sensors have several disadvantages from the standpoint of drive cost, reliability, inertia and noise immunity. Advantages of eliminating speed sensors thus have been a strong motivation to develop speed sensor less induction motor drives for industrial drives. Several control strategies of sensor less control are available in literature. This paper is an attempt to explore the possibility of estimation of rotor speed with the help of extended Kalman filter trained recurrent Neural Network. The speed estimation is made robust by simultaneously adapting the rotor resistance and rotor flux which are also done by the same Neural Network. The training is very fast as it requires only one iteration. The proposed scheme is studied on an induction motor and it gives better performance as compared to the already existing algorithms in the literature.
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Geetha, E.,Chakravarty, A.K.,Vinaya Kumar, K. Asian Australasian Association of Animal Productio 2006 Animal Bioscience Vol.19 No.12
A random regression model was applied for the first time for the analysis of test day records and to study the genetic persistency of first lactation milk yield of Indian Murrah buffaloes. Wilmink's Function was chosen to describe the shape of lactation curves. Heritabilities of test day milk yield varied from 0.33 to 0.58 in different test days. The highest heritability was found in the initial test day ($5^{th}$ day) milk yield. Genetic correlations among test day milk yields were higher in the initial test day milk yield and decreased when the test day interval was increased. The magnitude of genetic correlations between test day and 305 day milk yield varied from 0.25 to 0.99. The genetic persistencies of first lactation milk yield were estimated based on daily breeding values using two methods. $P_1$ is the genetic persistency estimated as a summation of the deviation of estimated daily breeding value on days to attain peak yield from each day after days to attain peak yield to different lactation days. $P_2$ is the genetic persistency estimated as the additional genetic yield (gained or lost) from days to attain peak yield to estimated breeding value on different lactation days relative to an average buffalo having the same yield on days to attain peak yield. The mean genetic persistency on 90, 120, 180, 240, 278 and 305 days in milk was estimated as -4.23, -21.67, -101.67, -229.57, -330.06 and -388.64, respectively by $P_1$, whereas by $P_2$ on same days in milk were estimated as -3.96 (-0.32 kg), -23.94 (-0.87 kg), -112.81 (-1.96 kg), -245.83 (-2.81 kg), -350.04 (-3.28 kg) and -407.58 (-3.40 kg) respectively. Higher magnitude of rank correlations indicated that the ranking of buffaloes based on their genetic persistency in both methods were similar for evaluation of genetic persistency of buffaloes. Based on the estimated range of genetic persistency three types of genetic persistency were identified. Genetic correlations among genetic persistency in different days in milk and between genetic persistencies on the same day in milk were very high. The genetic correlations between genetic persistency for different days in milk and estimated breeding value for 305 DIM was increased from 90 DIM to 180 DIM, and highest around 240 DIM which indicates a minimum of 240 days as an optimum first lactation length might be required for genetic evaluation of Indian Murrah buffaloes.
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