def run(dlc=None, dlc_noipc=None, SAVE=None):
wsp = 18
# Load transfer functions
C = make()
P = BladeModel.Blade(wsp)
Kps, Tis = np.meshgrid([0.01, 0.015, 0.02], [0.5, 1, 2])
fig, axes = plt.subplots(3, 3, sharex=False, sharey=False, figsize=(7, 7))
plt.subplots_adjust(wspace=0.05, hspace=0.05)
for i in range(3):
for j in range(3):
C = make(Kp=Kps[i, j], Ti=Tis[i, j])
sys = ControlDesign.Turbine(P, C)
plot_nyquist(sys.L, axes=axes[i, j], zoom=1, margin=True)
perf = sys.performance(0.16)[0]
axes[i, j].text(0,
0,
'$f_{1p}$: ' + '{:2.2f}\%'.format(perf * 100),
transform=axes[i, j].transAxes,
va='bottom')
fig.text(0.1, 0.5, 'Real', va='center', rotation='vertical')
fig.text(0.5, 0.1, 'Imaginary', ha='center', rotation='horizontal')
for i in range(3):
axes[0, i].set_title(f'$K_p=${Kps[0, i]}')
axes[i, 2].yaxis.set_label_position('right')
axes[i, 2].set_ylabel(f'$T_i=${Tis[i, 0]}')
if SAVE:
plt.savefig(SAVE, dpi=200, bbox_inches='tight')
plt.show()
print()
def run(dlc=None, dlc_noipc=None, SAVE=None):
f = np.linspace(0, 1.5, 1000)[1:]
Yol = OLResponse.Response(18)
Ycl = Spectrum(dlc(wsp=18, controller='ipcpi')[0])
C = make()
P = BladeModel.Blade(18)
sys = ControlDesign.Turbine(P, C)
mag = signal.bode(sys.S, w=f * (2 * np.pi))[1]
actualMag = 20 * np.log10(Ycl(f) / Yol(f))
fig, ax = ControllerEvaluation.magplotSetup(F1p=0.16)
ax.set_xlim(0.05, 1.5)
ax.axhline(0, lw=1, c='0.8', ls='-')
ax.plot(f, mag, label='$S(C_{PI})$, linear model')
ax.plot(f, actualMag, '--', label='$S(C_{PI})$, HAWC2 model')
ax.set_ylim(-10, 10)
ax.legend(loc='upper left')
if SAVE:
plt.savefig(SAVE, dpi=200, bbox_inches='tight')
plt.show()
print()
def run(dlc=None, dlc_noipc=None, SAVE=None):
wsp = 18
C = make()
P = BladeModel.Blade(wsp)
sys = ControlDesign.Turbine(P, C)
plot_nyquist(sys.L, zoom=1.5, rightticks=True, save=SAVE)
def run(dlc=None, dlc_noipc=None, SAVE=None):
f = np.linspace(0, 1.5, 1000)[1:]
Yol = OLResponse.Response(18)
Ycl = Spectrum(dlc(wsp=18, controller='ipcpi')[0])
C = make()
P = BladeModel.Blade(18)
sys = ControlDesign.Turbine(P, C)
mag = signal.bode(sys.S, w=f * (2 * np.pi))[1]
#actualMag = 20*np.log10(Ycl(f)/Yol(f))
w, H = signal.freqresp(sys.S, n=100000)
f = w / (2 * np.pi)
Ycl_pred = abs(H) * Yol(f)
fig, ax = ControllerEvaluation.magplotSetup(F1p=0.16)
ax.set_xlim(0.05, 1.5)
ax.axhline(0, lw=1, c='0.8', ls='-')
ax.plot(f, Yol(f), label='Open loop')
ax.plot(f, Ycl_pred, '--k', label='Closed loop (linear)')
ax.plot(f, Ycl(f), 'r', label='Closed loop (HAWC2)')
#ax.plot(f, mag, label='$S(C_{PI})$, linear model')
#ax.plot(f, actualMag, '--', label='$S(C_{PI})$, HAWC2 model')
ax.set_ylabel('Magnitude [m]')
ax.set_xlim(0.05, 1.5)
ax.set_ylim(0.01, 0.4)
ax.set_yscale('log')
ax.legend(loc='upper right')
if SAVE:
plt.savefig(SAVE, dpi=200, bbox_inches='tight')
plt.show()
print()
ax.plot(f, Yol(f), label='$Y_{OL}$')
ax.plot(f, Ycl_pred, '--k', label='$Y_{CL}$ (predicted)')
ax.plot(f, Ycl(f), 'r', label='$Y_{CL}$ (actual)')
ax.set_xlim(f.min(), 1.5)
ax.set_title('wsp = {}m/s'.format(wsp))
ax.legend()
if SAVE:
plt.savefig(
'../Figures/{}/{}_TipDeflection_Spectrum_{}.png'.format(
c, c, wsp),
dpi=200)
plt.show()
print()
for f in fnp:
pred = abs(signal.freqresp(system.S,
f * 2 * np.pi)[1][0]) * 100 - 100
act = Ycl(f) / Yol(f) * 100 - 100
print('{:2.2f}%, {:2.2f}%'.format(pred, act))
if __name__ is '__main__':
dlc_noipc = PostProc.DLC('dlc11_0')
dlc = PostProc.DLC('dlc11_1')
from Controllers.IPC_PI import make
c = 'ipcpi'
run(dlc, dlc_noipc, c, make(), SAVE=False)
def discretise(C, Fs=100, method='bilinear', save=None):
# discretizes the controller transfer function and saves it to file.
if method == 'bilinear':
coefz = signal.bilinear(C.num, C.den, fs=Fs)
elif method.lower() == 'matchedzeropole':
coefz = MatchedZeroPole(C.num, C.den, 1 / Fs)
Cd = signal.TransferFunction(coefz[0], coefz[1], dt=1 / Fs)
return Cd
if __name__ == '__main__':
C = make()
Cd = discretise(C, Fs=Fs)
saveHTC(Cd.num, Cd.den, filename)
# Calculate continuous frequency response
wa, maga, phasea = signal.bode(C, n=1000)
phasea = (phasea + 180) % 360 - 180
fa = wa / (2 * np.pi)
# calculate discrete frequency response
wd, Hd = signal.freqz(Cd.num, Cd.den, worN=1024 * 4)
fd = wd / np.pi * (Fs / 2)
magd, phased = 20 * np.log10(abs(Hd)), np.angle(Hd, deg=True)
# plot