def calcular(self, n, norm=False, k_factor=1):
# Atencion: Norm = calcular normalizada
if n % 2 == 1:
k = int((n - 1) / 2)
arr = []
for i in range(k + 1):
arr.append(get_a(i, n))
poly = legendre.leg2poly(legendre.legint(legendre.legmul(arr,
arr)))
else:
k = int((n - 2) / 2)
arr = []
for i in range(k + 1):
arr.append(get_a(i, n))
leg_b = legendre.legmul(legendre.legmul(arr, arr),
legendre.poly2leg([1, 1]))
poly = legendre.leg2poly(legendre.legint(leg_b))
exp = 0
wn, sn, s, sa = sp.symbols("wn sn sa s")
for i in range(len(poly)):
exp += poly[i] * ((2 * (wn**2) - 1)**i)
exp -= poly[i] * ((-1)**i)
if n % 2 == 1:
exp = exp * 1 / (2 * (k + 1)**2)
else:
exp = exp * 1 / ((k + 1) * (k + 2))
exp = 1 / (1 + self.getXi(0, n)**2 * exp)
exp = exp.subs(wn, sn / 1j)
roots = algebra.getRoots(exp, sn)
roots[1] = algebra.filterRealNegativeRoots(roots[1])
poles = []
for i in roots[1]:
poles.append({"value": i})
exp = algebra.armarPolinomino(poles, [], sn, 1)
self.tf_normalized = algebra.conseguir_tf(exp, sn, poles)
if not norm:
exp = self.plantilla.denormalizarFrecuencias(exp, sa, sn)
self.getGainPoints()
factor = (self.k1 - self.k2) * norm / 100 + self.k2
exp = self.plantilla.denormalizarAmplitud(exp, s, sa, factor)
self.tf = algebra.conseguir_tf(exp, s, [])
return self.tf
else:
return self.tf_normalized
def calcularDadoGamma(self, n_value, k=1, norm=-1, gamma=1):
sn, s = sp.symbols("sn s")
#print(num)
den = 0
fact = 1
cnt = -1
for i in range(1, n_value + 1):
fact *= i
den += (gamma**i) * ((s / sp.I)**(2 * i)) / fact
#print(den)
exp = 1 / (1 + den)
#exp = self.plantilla.denormalizarFrecuencias(exp, s, sn)
#print(exp)
roots = algebra.getRoots(exp, s)
roots[1] = algebra.filterRealNegativeRoots(roots[1])
poles = []
for i in roots[1]:
poles.append({"value": i})
exp = algebra.armarPolinomino(poles, [], s, 1)
self.tf = algebra.conseguir_tf(exp, s, [])
return self.tf
def calcular(
self,
n_value,
norm,
k=1
): # calcular mediante N la funcion transferencia de la aproximacion
poles = self.getPoles(n_value, self.getXi(norm, n_value))
zeroes = self.getZeroes(n_value, self.getXi(norm, n_value))
sn, sa, s = sp.symbols("sn sa s")
pol = armarPolinomino(poles, zeroes, sn, self.getZeroGain(n_value))
self.tf_normalized = conseguir_tf(pol, sn, poles)
self.getGainPoints()
factor = (self.k1 - self.k2) * norm / 100 + self.k2
pol = self.plantilla.denormalizarAmplitud(pol, sa, sn, factor)
#pol = self.plantilla.denormalizarAmplitud(pol, sa, sn, n_value, 1, 0)
pol = self.plantilla.denormalizarFrecuencias(pol, s, sa)
#print(pol)
self.tf = conseguir_tf(pol, s, poles)
self.updateEtapas()
return self.tf
def calcular(self, n_value, k=1, norm = -1):
sn, s = sp.symbols("sn s")
self.var = s
num = computeBesselPoly(n_value, sn).evalf(subs={sn: 0})
#print(num)
den = computeBesselPoly(n_value, sn)
#print(den)
exp = num / den
exp = self.plantilla.denormalizarFrecuencias(exp, s, sn)
self.exp = exp
self.coef = algebra.conseguir_coef(exp, s)
self.tf = algebra.conseguir_tf(exp, s, [])
return self.tf
def computarMinMaxGain(
self, min_freq, max_freq
): # conseguir minima y maxima ganancia de la etapa dado un rango de frecuencias
self.tf = conseguir_tf(self.transfer_expression, self.var)
w, mag, pha = signal.bode(
self.tf, logspace(log10(min_freq), log10(max_freq), 10000))
self.w = w
self.mag = mag
minGain = 1e8
maxGain = -1e8
for m in self.mag:
minGain = min(minGain, m)
maxGain = max(maxGain, m)
self.minGain = minGain
self.maxGain = maxGain
if config.debug:
print("Ganancia mínima:", minGain)
print("Ganancia máxima:", maxGain)
s = sp.symbols('s')
Wo1 = 2 * pi * 12948.60
Q1 = 11.58
Wo2 = 2 * pi * 13850.42
Q2 = 3.65
Wo3 = 2 * pi * 15845.49
Q3 = 1.96
Wo4 = 2 * pi * 19525.55
Q4 = 1.19
Wo5 = 2 * pi * 25958.29
Q5 = 0.76
Wo6 = 2 * pi * 34110.10
Q6 = 0.53
H1 = veces(-0.10074052126957483) * s**2 / (s**2 + s * Wo1 / Q1 + Wo1**2)
H2 = veces(-0.10947355039605151) * s**2 / (s**2 + s * Wo2 / Q2 + Wo2**2)
H3 = veces(-0.12928908650773577) * s**2 / (s**2 + s * Wo3 / Q3 + Wo3**2)
H4 = veces(-0.1434825614451729) * s**2 / (s**2 + s * Wo4 / Q4 + Wo4**2)
H5 = veces(-0.035653959985164595) * s**2 / (s**2 + s * Wo5 / Q5 + Wo5**2)
H6 = veces(0.5186397040040062) * s**2 / (s**2 + s * Wo6 / Q6 + Wo6**2)
H = [H1, H2, H3, H4, H5, H6]
for i in range(len(H)):
if i != 0:
H[i] = H[i - 1] * H[i]
for i in range(len(H)):
H[i] = algebra.conseguir_tf(H[i], s)
Q4 = 1.19
Wo5 = 2 * pi * 25958.29
Q5 = 0.76
Wo6 = 2 * pi * 34110.10
Q6 = 0.53
H1 = s**2 / (s**2 + s * Wo1 / Q1 + Wo1**2)
H2 = s**2 / (s**2 + s * Wo2 / Q2 + Wo2**2)
H3 = s**2 / (s**2 + s * Wo3 / Q3 + Wo3**2)
H4 = s**2 / (s**2 + s * Wo4 / Q4 + Wo4**2)
H5 = s**2 / (s**2 + s * Wo5 / Q5 + Wo5**2)
H6 = s**2 / (s**2 + s * Wo6 / Q6 + Wo6**2)
conjunto = H1 * H2 * H3 * H4 * H5 * H6
w, mag, pha = signal.bode(algebra.conseguir_tf(conjunto, s), [1e7 * 2 * pi])
total_gain = -mag[0]
#
# print("total_gain = ", total_gain)
# conjunto = H1 * H2 * H3 * H4 * H5 * total_gain
#
# mag, pha, w = signal.bode(algebra.conseguir_tf(conjunto, s),1e6)
# total_gain = -mag[0]
print("total_gain = ", total_gain)
#
#
transf = [H1, H2, H3, H4, H5, H6]
transf = [etapas.EtapaEA(i, s) for i in transf]
transf[0].name = "1"
def __init__(self, expr, var):
self.tf = conseguir_tf(expr, var)
self.gain = 0
K = 0.162 C = 680e-12 a = 0.033 R2 = 20.5e3 H1 = (1/(1-K))*(a*s/(C*R1))/((s**2) + s*(2/(C*R2))*(1-(R2*K/(2*R1*(1-K)))) + (1/((C**2)*R1*R2))) R1 = 1.39e3 K = 0.165 C = 1e-9 a = 0.033 R2 = 12.6e3 H2 = (1/(1-K))*(a*s/(C*R1))/((s**2) + s*(2/(C*R2))*(1-(R2*K/(2*R1*(1-K)))) + (1/((C**2)*R1*R2))) H = H1*H2 #print(coef) K = 0.162 C = 470e-12 R2 = 29.7e3 Zin = 100000/(1 - H1*(((1-K)/(s*C*R2)) + K)) tf = algebra.conseguir_tf(H, s) tfZin = algebra.conseguir_tf(Zin, s)
R1 = 1.5e3
RA = 2.2e3
RB = 2e3
K = 1 + (RB / RA)
C = 100e-9
R2 = 1.5e3
a = 1.5 / 2.2
H2 = (a * K / (R1 * R2 * (C**2))) / ((s)**2 + s * (((1 / R1) +
((2 - K) / R2)) / (C)) +
(1 / (R1 * R2 * (C**2))))
Cf = 100e-9
Rf = 1.8e3
Rr = 2.9e3
H3 = Rf / (Rr * (s * Cf * Rf + 1))
bH = algebra.conseguir_tf(-H1 * H2 * H3, s)
R1 = 172e3
RA = 10e3
RB = 2.2e3
K = 1 + (RB / RA)
C = 1e-9
R2 = 172e3
a = 1
bZin = algebra.conseguir_tf(
R1 / (a * (1 - (H1 * RA * (s * C * R2 + 1) / (RA + RB)))), s)