116 lines
3.8 KiB
Python
Executable File
116 lines
3.8 KiB
Python
Executable File
#!/usr/bin/env python
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import csv
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import argparse
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# Using the method described in "Ziegler–Nichols Tuning Method∗" by Vishakha Vijay Patel
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# (https://www.ias.ac.in/article/fulltext/reso/025/10/1385-1397)
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def line(a, b, x):
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return a * x + b
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def invline(a, b, y):
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return (y - b) / a
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def plot(xdata, ydata,
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tangent_min, tangent_max, tangent_slope, tangent_offset,
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lower_crossing_x, upper_crossing_x):
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from matplotlib import pyplot
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minx = min(xdata)
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maxx = max(xdata)
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miny = min(ydata)
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maxy = max(ydata)
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pyplot.scatter(xdata, ydata)
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pyplot.plot([minx, maxx], [miny, miny], '--', color='purple')
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pyplot.plot([minx, maxx], [maxy, maxy], '--', color='purple')
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pyplot.plot(tangent_min[0], tangent_min[1], 'v', color='red')
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pyplot.plot(tangent_max[0], tangent_max[1], 'v', color='red')
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pyplot.plot([minx, maxx], [line(tangent_slope, tangent_offset, minx), line(tangent_slope, tangent_offset, maxx)], '--', color='red')
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pyplot.plot([lower_crossing_x, lower_crossing_x], [miny, maxy], '--', color='black')
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pyplot.plot([upper_crossing_x, upper_crossing_x], [miny, maxy], '--', color='black')
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pyplot.show()
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def calculate(filename, tangentdivisor, showplot):
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# parse the csv file
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xdata = []
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ydata = []
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filemintime = None
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with open(filename) as f:
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for row in csv.DictReader(f):
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try:
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time = float(row['pid_time'])
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temp = float(row['pid_ispoint'])
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if filemintime is None:
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filemintime = time
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xdata.append(time - filemintime)
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ydata.append(temp)
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except ValueError:
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continue # just ignore bad values!
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# gather points for tangent line
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miny = min(ydata)
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maxy = max(ydata)
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midy = (maxy + miny) / 2
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yoffset = int((maxy - miny) / tangentdivisor)
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tangent_min = tangent_max = None
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for i in range(0, len(xdata)):
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rowx = xdata[i]
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rowy = ydata[i]
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if rowy >= (midy - yoffset) and tangent_min is None:
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tangent_min = (rowx, rowy)
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elif rowy >= (midy + yoffset) and tangent_max is None:
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tangent_max = (rowx, rowy)
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# calculate tangent line to the main temperature curve
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tangent_slope = (tangent_max[1] - tangent_min[1]) / (tangent_max[0] - tangent_min[0])
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tangent_offset = tangent_min[1] - line(tangent_slope, 0, tangent_min[0])
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# determine the point at which the tangent line crosses the min/max temperaturess
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lower_crossing_x = invline(tangent_slope, tangent_offset, miny)
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upper_crossing_x = invline(tangent_slope, tangent_offset, maxy)
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# compute parameters
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L = lower_crossing_x - min(xdata)
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T = upper_crossing_x - lower_crossing_x
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# Magic Ziegler-Nicols constants ahead!
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Kp = 1.2 * (T / L)
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Ti = 2 * L
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Td = 0.5 * L
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Ki = Kp / Ti
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Kd = Kp * Td
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# outut to the user
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print(f"Kp: {Kp} 1/Ki: {1/ Ki}, Kd: {Kd}")
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if showplot:
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plot(xdata, ydata,
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tangent_min, tangent_max, tangent_slope, tangent_offset,
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lower_crossing_x, upper_crossing_x)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description='Perform Ziegler-Nichols PID tuning')
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parser.add_argument('csvfile', type=str, help="The CSV file to read from. Must contain two columns called pid_time (time in seconds) and pid_ispoint (observed temperature)")
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parser.add_argument('--showplot', action='store_true', help="If set, also plot results (requires pyplot to be pip installed)")
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parser.add_argument('--tangentdivisor', type=float, default=4, help="Adjust the tangent calculation to fit better. Must be >= 2.")
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args = parser.parse_args()
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if args.tangentdivisor < 2:
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raise ValueError("tangentdivisor must be >= 2")
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calculate(args.csvfile, args.tangentdivisor, args.showplot)
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