HU-Projects/pid-balancer
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# Conflicts:
#	control_functions.py
This commit is contained in:
Rudi klein 2024-12-29 22:02:37 +01:00
commit 6608ecc8bf
3 changed files with 100 additions and 78 deletions
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123
control_functions.py
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@ -1,6 +1,6 @@
from adafruit_hcsr04 import HCSR04 as hcsr04 # PWM driver board for servo
import board # PWM driver board for servo
from adafruit_servokit import ServoKit # Servo libraries
from adafruit_hcsr04 import HCSR04 as hcsr04 # Ultrasound sensor
import board # General board pin mapper
from adafruit_servokit import ServoKit # Servo libraries for PWM driver board
import adafruit_pcf8591.pcf8591 as PCF # AD/DA converter board for potentiometer
from adafruit_pcf8591.analog_in import AnalogIn # Analogue in pin library
from adafruit_pcf8591.analog_out import AnalogOut # Analogue out pin library
@ -14,8 +14,6 @@ import csv # CSV handling
from datetime import datetime # Date and time formatting
import time # Time formatting
######################################## Variables (start) ##################################
# Variables to control sensor
TRIGGER_PIN = board.D4 # GPIO pin xx
ECHO_PIN = board.D17 # GPIO pin xx
@ -34,49 +32,52 @@ LOG: bool = True # Log data to files
SCREEN: bool = True # Log data to screen
DEBUG: bool = False # More data to display
# Control the number of samples for single measurement
MAX_SAMPLES = 10
# Control the number of samples for the potentiometer
PCF_VALUE = 65535
POT_MAX = 65280
POT_MIN = 256
POT_INTERVAL = 0.1
# Variables to assist PID calculations
current_time = 0
integral = 0
time_prev = -1e-6
error_prev = 0
current_time: float = 0
integral: float = 0
time_prev: float = -1e-6
error_prev: float = 0
# Variables to control PID values (PID formula tweaks)
p_value = 2
i_value = 0
d_value = 0
p_value : float = 2.0
i_value: float = 0.0
d_value: float = 0.0
# Initial variables, used in pid_calculations()
i_result = 0
previous_time = 0
previous_error = 0
i_result: float = 0.0
previous_time: float = 0.0
previous_error: float = 0.0
# Init array, used in read_distance_sensor()
sample_array: list = []
######################################## Variables (end) ##################################
def initial():
...
# Create timestamp strings for logs and screen
def time_stamper():
log_timestamp: str = datetime.strftime(datetime.now(), '%Y%m%d%H%M%S.%f')[:-3]
file_timestamp: str = datetime.strftime(datetime.now(), '%Y%m%d%I%M')
return log_timestamp, file_timestamp
# Write data to any of the logfiles
def log_data(fixed_file_stamp: str, data_file: str, data_line: float, remark: str|None):
log_stamp, _ = time_stamper()
def log_data(file_stamp: str, data_file: str, data_line: float, remark: str|None):
log_stamp: str = datetime.strftime(datetime.now(), '%Y%m%d%H%M%S.%f')[:-3]
with open("pid-balancer_" + data_file + "_data_" + fixed_file_stamp + ".csv", "a") as data_file:
with open("pid-balancer_" + data_file + "_data_" + file_stamp + ".csv", "a") as data_file:
data_writer = csv.writer(data_file)
data_writer.writerow([log_stamp,data_line, remark])
def read_distance_sensor(fixed_file_stamp):
def read_distance_sensor(file_stamp):
with (hcsr04(trigger_pin=TRIGGER_PIN, echo_pin=ECHO_PIN, timeout=TIMEOUT) as sonar):
# Do a burst (MAX_SAMPLES) of measurements, filter out the obvious wrong ones (too short or to long distance)
# Return the mean timestamp and median distance.
with hcsr04(trigger_pin=TRIGGER_PIN, echo_pin=ECHO_PIN, timeout=TIMEOUT) as sonar:
samples: int = 0
max_samples: int = 10
max_samples: int = MAX_SAMPLES
timestamp_last: float = 0.0
timestamp_first: float = 0.0
while samples != max_samples:
@ -84,12 +85,14 @@ def read_distance_sensor(fixed_file_stamp):
distance: float = sonar.distance
if MIN_DISTANCE < distance < MAX_DISTANCE:
log_data(fixed_file_stamp,"sensor", distance, None) if LOG else None
log_data(file_stamp,"sensor", distance, None) if LOG else None
print("Distance: ", distance) if SCREEN else None
sample_array.append(distance)
if samples == 0: timestamp_first, _ = time_stamper()
if samples == max_samples - 1: timestamp_last, _ = time_stamper()
if samples == 0: timestamp_first = float(datetime.strftime(datetime.now(),
'%Y%m%d%H%M%S.%f')[:-3])
if samples == max_samples - 1: timestamp_last = float(datetime.strftime(datetime.now(),
'%Y%m%d%H%M%S.%f')[:-3])
timestamp_first_float: float = float(timestamp_first)
timestamp_last_float: float = float(timestamp_last)
@ -100,45 +103,37 @@ def read_distance_sensor(fixed_file_stamp):
print(mean_timestamp) if SCREEN else None
else:
log_data(fixed_file_stamp,"sensor", distance,"Ignored") if LOG and DEBUG else None
log_data(file_stamp,"sensor", distance,"Ignored") if LOG and DEBUG else None
print("Distance: ", distance) if SCREEN else None
except RuntimeError:
log_data(fixed_file_stamp, "sensor", 999.999, "Timeout") if LOG and DEBUG else None
log_data(file_stamp, "sensor", 999.999, "Timeout") if LOG and DEBUG else None
print("Timeout") if SCREEN else None
return median_distance, mean_timestamp
def read_setpoint():
############# AnalogOut & AnalogIn Example ##########################
#
# This example shows how to use the included AnalogIn and AnalogOut
# classes to set the internal DAC to output a voltage and then measure
# it with the first ADC channel.
#
# Wiring:
# Connect the DAC output to the first ADC channel, in addition to the
# normal power and I2C connections
#
#####################################################################
i2c = board.I2C()
pcf = PCF.PCF8591(i2c)
pcf_in_0 = AnalogIn(pcf, PCF.A0)
pcf_out = AnalogOut(pcf, PCF.OUT)
pcf_out.value = PCF_VALUE
while True:
print("Setting out to ", 65535)
pcf_out.value = 65535
raw_value = pcf_in_0.value
scaled_value = (raw_value / 65535) * pcf_in_0.reference_voltage
raw_value: float = pcf_in_0.value
scaled_value: float = (raw_value / PCF_VALUE) * pcf_in_0.reference_voltage
# Calculate angle in reference to raw pot values
angle: float = ((180 - 0) / (POT_MAX - POT_MIN)) * (raw_value - POT_MIN)
print("Pin 0: %0.2fV" % (scaled_value))
print("")
time.sleep(1)
if SCREEN:
print('pin 0 ', pcf.read(0))
print('raw_value ',raw_value)
print("pin 0: %0.2fV" % scaled_value)
print(angle)
time.sleep(POT_INTERVAL)
send_data_to_servo(set_angle=angle)
def calculate_velocity():
...
@ -147,7 +142,7 @@ def pid_calculations(setpoint):
global i_result, previous_time, previous_error
offset_value: int = 320
measurement, current_time = read_distance_sensor
measurement, measurement_time = read_distance_sensor()
error: float = setpoint - measurement
error_sum: float = 0.0
@ -157,22 +152,24 @@ def pid_calculations(setpoint):
i_result = 0.0
error_sum = error * 0.008 # sensor sampling number approximation.
error_sum = error_sum + (error * (current_time - previous_time))
p_result = p_value * error
error_sum: float = error_sum + (error * (current_time - previous_time))
p_result = p_value * error
i_result = i_value * error_sum
d_result = d_value * ((error - previous_error) / (current_time - previous_time))
d_result = d_value * ((error - previous_error) / (measurement_time - previous_time))
pid_result = offset_value + p_result + i_result + d_result
previous_error = error
previous_time = current_time
previous_error = error
previous_time = measurement_time
return pid_result
def calculate_new_servo_pos():
def calculate_new_servo_position():
...
def send_data_to_servo():
def send_data_to_servo(set_angle):
KIT.servo[0].angle = 180 # Set angle
KIT.servo[0].angle = set_angle # Set angle
read_distance_sensor(file_stamp=123)
read_setpoint()

14
main.py
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@ -1,17 +1,9 @@
from datetime import datetime
import control_functions as cf
import plotter_functions as pf
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint
import numpy as np
import matplotlib.pyplot as plt
import statistics as st
from adafruit_hcsr04 import HCSR04 as hcsr04
_, fixed_file_stamp = cf.time_stamper()
file_stamp: str = datetime.strftime(datetime.now(), '%Y%m%d%I%M')
cf.read_distance_sensor(fixed_file_stamp)
cf.read_distance_sensor(file_stamp)

41
plotter_functions.py
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@ -1,7 +1,40 @@
def read_data_file():
pass
import pandas as pd
import matplotlib.pyplot as plt
# Variables to control logging.
LOG: bool = True # Log data to files
SCREEN: bool = True # Log data to screen
DEBUG: bool = False # More data to display
def plot_graphs():
pass
def read_data_file(data_file):
data_frame = pd.read_csv(data_file)
first_row_time = data_frame['Timestamp'].iloc[1]
last_row_time = data_frame['Timestamp'].iloc[-1]
first_row_value = data_frame['Value'].iloc[1]
last_row_value = data_frame['Value'].iloc[-1]
mean_value = data_frame['Value'].mean()
median_value = data_frame['Value'].median()
sum_value = data_frame['Value'].sum()
if SCREEN:
print('first_row_value ',first_row_value)
print('last_row_value ',last_row_value)
print('first_row_time ', first_row_time)
print('last_row_time ', last_row_time)
print('elapsed_time ', (last_row_time - first_row_time))
print('mean_value ', mean_value)
print('median_value ', median_value)
print('sum_value ', sum_value)
return data_frame
def plot_data_frame(data_file):
data_frame = read_data_file(data_file)
plt.plot(data_frame['Timestamp'], data_frame['Value'])
# plt.savefig(data_file + '.png')
# img = plt.imread(data_file + '.png')
# plt.imshow(img)
plt.show()
plot_data_frame(data_file = 'pid-balancer_twin_test_data.csv')