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Controlling soil moisture using a PID controller

Now we can change our PID controller simulation using a real application. We use soil moisture to decide whether to pump water. The output of the measurement is used as feedback input for the PID controller.

If the PID output is a positive value, then we turn on the watering system. Otherwise, we stop it. This may not be a good approach but is a good way to show how PID controllers work. Soil moisture data is obtained from the Arduino through a wireless network.

Let's write this program:

import matplotlib 
matplotlib.use('Agg')

import PID
import time
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import spline

P = 1.4
I = 1
D = 0.001
pid = PID.PID(P, I, D)

pid.SetPoint = 0.0
pid.setSampleTime(0.25) # a second

total_sampling = 100
sampling_i = 0
measurement = 0
feedback = 0

feedback_list = []
time_list = []
setpoint_list = []


def get_soil_moisture():
# reading from Arduino
# value 0 - 1023
return 200



print('PID controller is running..')
try:
while 1:
pid.update(feedback)
output = pid.output

soil_moisture = get_soil_moisture()
if soil_moisture is not None:

# # ## testing
# if 23 < sampling_i < 50:
# soil_moisture = 300

# if 65 <= sampling_i < 75:
# soil_moisture = 350

# if sampling_i >= 85:
# soil_moisture = 250
# # ################

if pid.SetPoint > 0:
feedback += soil_moisture + output

print('i={0} desired.soil_moisture={1:0.1f} soil_moisture={2:0.1f} pid.out={3:0.1f} feedback={4:0.1f}'
.format(sampling_i, pid.SetPoint, soil_moisture, output, feedback))
if output > 0:
print('turn on watering system')
elif output < 0:
print('turn off watering system')

if 20 < sampling_i < 60:
pid.SetPoint = 300 # soil_moisture

if 60 <= sampling_i < 80:
pid.SetPoint = 200 # soil_moisture

if sampling_i >= 80:
pid.SetPoint = 260 # soil_moisture



time.sleep(0.5)
sampling_i += 1

feedback_list.append(feedback)
setpoint_list.append(pid.SetPoint)
time_list.append(sampling_i)

if sampling_i >= total_sampling:
break

except KeyboardInterrupt:
print("exit")


print("pid controller done.")
print("generating a report...")
time_sm = np.array(time_list)
time_smooth = np.linspace(time_sm.min(), time_sm.max(), 300)
feedback_smooth = spline(time_list, feedback_list, time_smooth)

fig1 = plt.gcf()
fig1.subplots_adjust(bottom=0.15, left=0.1)

plt.plot(time_smooth, feedback_smooth, color='red')
plt.plot(time_list, setpoint_list, color='blue')
plt.xlim((0, total_sampling))
plt.ylim((min(feedback_list) - 0.5, max(feedback_list) + 0.5))
plt.xlabel('time (s)')
plt.ylabel('PID (PV)')
plt.title('Soil Moisture PID Controller')


plt.grid(True)
fig1.savefig('pid_soil_moisture.png', dpi=100)
print("finish")

Save this program to a file called ch01_pid.py and run it like this:

    $ sudo python ch01_pid.py  

After executing the program, you should obtain a file called pid_soil_moisture.png. A sample output can be seen in the following figure:

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