pyblocksim/examples/example2.py at main · TUD-RST/pyblocksim · GitHub

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# -*- coding: utf-8 -*-

from pyblocksim import *

mainprint(
    """
Example2 : linear system consiting of various blocks

 (coupled linear transfer functions)
"""
)

fb1, fb2, w, z11, z21, z12, z22 = inputs("fb1, fb2, w, z11, z21, z12, z22")

# The two PI controllers (naively parameterized by neglecting the coupling):
KR1 = 1.7
TN1 = 1.29

KR2 = 0.57
TN2 = 1.29

### Plant
T1 = 1.0

# equilibrium pojnt 1
K1, K2, K3, K4 = 0.4, 1.2, -0.8, -0.2

# equilibrium point 2
# K1, K2, K3, K4 = 0.4, 1.2, -1.28, -0.32

# switch of coupling:
# K3, K4 = 0,0


DIF1 = Blockfnc(w - fb1)
DIF2 = Blockfnc(-fb2)

PI1 = TFBlock(KR1 * (1 + 1 / (s * TN1)), DIF1.Y)
PI2 = TFBlock(KR2 * (1 + 1 / (s * TN2)), DIF2.Y)

SUM11 = Blockfnc(PI1.Y + z11)
SUM21 = Blockfnc(PI1.Y + z21)

SUM12 = Blockfnc(PI2.Y + z12)
SUM22 = Blockfnc(PI2.Y + z22)

P11 = TFBlock(K1 / s, SUM11.Y)
P21 = TFBlock(K4 / (1 + s * T1), SUM21.Y)
P12 = TFBlock(K3 / s, SUM12.Y)
P22 = TFBlock(K2 / s, SUM22.Y)

SUM1 = Blockfnc(P11.Y + P12.Y)
SUM2 = Blockfnc(P22.Y + P21.Y)

loop(SUM1.Y, fb1)
loop(SUM2.Y, fb2)

thestep = stepfnc(1.0, 1)

t, states = blocksimulation(40, (w, thestep), dt=0.05)

bo = compute_block_outputs(states)

if __name__ == "__main__":
    pl.plot(t, bo[SUM1])
    pl.plot(t, bo[P22])
    pl.plot(t, bo[P11])
    pl.grid()
    pl.show()