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# Untitled

a guest Dec 16th, 2018 56 Never
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1. import numpy as np
2. import matplotlib.pyplot as plt
3. import scipy.optimize as scp
4.
5.
6.
7. def myFunc(K):
8.     T = 30
9.     h = 0.01
10.     y = 0
11.     x = 1
12.     xThres = 0
13.     error=0
14.
15.     a = 0.7
16.     b = 0.7
17.     c = 3
18.     z = -0.4
19.     columns = (T // h) + 1
20.     table = np.zeros(shape=(3, int(columns)))
21.     tableU = np.zeros(shape=(2, int(columns)))
22.     tableE = np.zeros(shape=(2, int(columns)))
23.     table[0][0] = y
24.     table[1][0] = x
25.     tableE[0][0] = xThres - x
26.     e_sum = tableE[0, 0] * h
27.     tableU[0, 0] = K[0] * tableE[0, 0] + K[1] * e_sum
28.     if tableU[0, 0] > 2:
29.         tableU[0, 0] = 2
30.     elif tableU[0, 0] < -2:
31.         tableU[0, 0] = -2
32.     nextX = x
33.     nextY = y
34.
35.     for j in range(1, int(columns)):
36.         table[0, j] = nextY + (-(1 / c) * (nextX - a + b * nextY)) * h
37.         nextY = table[0, j]
38.         table[1, j] = nextX + (c * (nextY - ((nextX * nextX * nextX) / 3) + nextX + z) + tableU[0, j - 1]) * h
39.         nextX = table[1, j]
40.         table[2, j] = table[2, j - 1] + h
41.         e_pop = tableE[0, j - 1]
42.         tableE[0, j] = xThres - nextX
43.         e_sum += tableE[0, j] * h
44.         tableU[0, j] = K[0] * tableE[0, j] + K[1] * e_sum + K[2] * ((-e_pop + tableE[0, j]) / h)
45.         if tableU[0, j] > 2:
46.             tableU[0, j] = 2
47.         elif tableU[0, j] < -2:
48.             tableU[0, j] = -2
49.         tableU[1, j] = tableU[1, j - 1] + h
50.         tableE[1, j] = tableE[1, j - 1] + h
51.         error += abs(tableE[0, j]) * tableE[1, j]
52.     return error
53.
54.
55. print(scp.fmin_bfgs(myFunc,[1,1,1]))
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