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38.4.ANN-based Controls in Motor Drives > 38.4.ANN-based Controls in Motor Driv... - Pg. 1150

1150 ^ R r 9 R r 8 (W) (i) 7 6 ^ R r R r B. Karanayil and M. F. Rahman 8 T e (Nm) (ii) 7.5 7 Without RRE and SRE With RRE and without SRE With RRE and SRE 1.1 l rd (Wb) (iii) 1 0.9 12 10 (W) (iv) 8 6 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 2.2 R s R s ^ R s Time (second) FIGURE 38.24 Performance of the drive with and without RRE and SRE using ANN for 40% step change in R r and R s , R r and R s compensated ­ modeling results. 6 15 Stator current (Amp) 4 R s 10 (W) 5 3.4W added in series 0 5 4 ^ R r (W) 3 2 1 0 0.5 1 1.5 2 2.5 3 3.5 4 ^ R s 2 0 -2 -4 -6 0 0.01 s i ds (k) s i ds * (k) Estimated by neural network Measured 0.02 Time (second) 0.03 0.04 FIGURE 38.26 Stator currents in R s estimation ­ experimental results. Time (second) FIGURE 38.25 Estimated stator resistance R s using ANN ­ experimen- tal results. This is done for fixed number of trials and after each trial, the error with the desired output is computed. Finally, the set of weight changes which result in the least error are chosen and the whole process is repeated till convergence is reached. The modeling results reported in this scheme was excellent. Later, Burton et al. presented their practical implementation