Algorithm Of Sequential Gradient Search Essay

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3.6. Algorithm of sequential gradient search Step 1: Set specifications of the inductor Step 2: Set the values of Bm ,  and no. of core steps. Step 3: 0.45≤ K ≤ 0.6 and 0.3 ≤ Rw ≤ 0.4 Step 4: i = 0 to 30 do: K  0.3  i / 100 Step 5: Calculate cost. Step 6: If cost shows initially low and after that high, (concavity fails for K ) go to step 28 Step 7: i = 0 to 20 do: Rw  2  i /10 Step 8: Go to sub-routine, calculate the cost. Step 9: If cost does not show low value and then high (concavity fails for Rw ) go to step 28 Step 10: i = 0 to 30 do: K  0.3  i / 100 Step 11: Go to sub-routine and calculate the cost. Step 12: if present cost > previous cost go to step 14 Step 13: end for Step 14: back to previous value of K Step 15: For i = 0 to 20 do: Rw  2  i /10 Step 16: Go to sub-routine and calculate the cost. Step 17: if present cost > previous cost go to step 19 Step 18: end for Step 19: back to previous value of Rw Step 20: Go to sub-routine and calculate cost, performance etc. Step21: check for constraints violation (iron loss &copper loss), if it violets then go to step 25 Step 22: check for temperature rise, if it violets then go to step 25 Step 23: Print out results: go to step 26 Step 24: Stop Step 25: End Design optimization or optimal Design means effective and efficient design with minimum manufacturing cost within certain restriction imposed on it. Optimization is the process of searching highest and the least values of a given
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