Python PLC: Programmable Logic Controller written in Python
Python PLC: A Programmable Logic Controller Written in Python
1. Overview
A programmable logic controller (PLC) is a device commonly used in automation control. It implements various logic control tasks through programming. Traditional PLC programming languages are complex and have a steep learning curve. However, Python, as a simple and easy-to-learn scripting language, is increasingly being used for PLC programming. This article will provide a detailed introduction to programmable logic controllers written in Python.
2. Basic Principles of Python PLC
Python The basic principle of PLC is to implement various logical control tasks by writing Python programs. Programmers can use Python to write various control logic and execute this logic through the PLC. Python PLCs typically need to communicate with hardware devices (such as sensors and actuators) to sense and control the external environment.
3. Python PLC Implementation Methods
There are many ways to implement Python PLCs. The following describes two common implementations.
3.1 Running Python Scripts on Industrial Computers
In this implementation, the Python script runs directly on the industrial computer and communicates with the hardware devices through the computer’s interfaces. The Python script can use specific library functions to implement hardware communication and control operations. This approach offers high programming flexibility and allows the use of Python’s powerful library functions to implement complex control logic. However, some knowledge of hardware and operating systems is also required.
3.2 Running Python Scripts Directly on Embedded Devices
In this implementation, Python scripts run directly on embedded devices, which typically integrate the hardware interfaces required by PLCs, such as GPIO and serial ports. Python scripts can communicate with and control the hardware by calling the embedded device’s API. This approach offers the advantages of low hardware cost and compact size, making it suitable for scenarios with relatively simple hardware requirements.
4. Python PLC Example Code
The following five example code examples demonstrate Python PLC application scenarios and specific implementations.
4.1 Controlling the LED Light On and Off
import RPi.GPIO as GPIO
import time
# Set the GPIO port to output mode
GPIO.setmode(GPIO.BCM)
GPIO.setup(20, GPIO.OUT)
# Turn the LED light on and off
def toggle_led():
GPIO.output(20, GPIO.HIGH)
time.sleep(1)
GPIO.output(20, GPIO.LOW)
time.sleep(1)
# Loop to turn the light on and off
while True:
toggle_led()
This example code demonstrates how to use Python to control the LED light on and off on an embedded device. By continuously looping to turn the light on and off, a blinking effect is achieved.
4.2 Temperature Control System
import Adafruit_DHT
# Pin number of the temperature and humidity sensor
sensor = Adafruit_DHT.DHT11
pin = 4
# Get temperature and humidity data
def get_temperature_humidity():
humidity, temperature = Adafruit_DHT.read_retry(sensor, pin)
return humidity, temperature
# Control temperature
def control_temperature():
humidity, temperature = get_temperature_humidity()
if temperature > 30:
# Turn on the fan
print("Turn on the fan.")
elif temperature < 20:
# Turn on the heater
print("Turn on the heater.")
else:
# Turn off the fan and heater
print("Turn off the fan and heater.")
# Loop through the temperature control operations
while True:
control_temperature()
This sample code demonstrates how to use Python to control the temperature of a temperature control system. By continuously acquiring temperature and humidity data, the current temperature is determined and the fan and heater are controlled based on the set thresholds.
4.3 Motor Control
import RPi.GPIO as GPIO
import time
# Set the GPIO port to output mode
GPIO.setmode(GPIO.BCM)
GPIO.setup(26, GPIO.OUT)
# Control the motor
def control_motor():
GPIO.output(26, GPIO.HIGH)
time.sleep(1)
GPIO.output(26, GPIO.LOW)
# Loop to execute motor control operations
while True:
control_motor()
This sample code demonstrates how to use Python to control the motor on an embedded device. By looping through the motor control operations, the motor achieves continuous rotation.
4.4 Serial Communication
import serial
# Open the serial port and communicate
ser = serial.Serial('/dev/ttyUSB0', 9600)
def communicate():
# Read serial port data
data = ser.readline()
# Process received data
if data.strip() == b'ON':
# Send a command to turn the light on and off
ser.write(b'LED_ON')
elif data.strip() == b'OFF':
# Send a command to turn the light off
ser.write(b'LED_OFF')
# Loop through serial communication operations
while True:
communicate()
This example code demonstrates using Python to communicate with another device via a serial port. By continuously receiving serial port data and sending corresponding instructions based on the received data, interaction with other devices is achieved.
4.5 Monitoring and Alarm System
import RPi.GPIO as GPIO
import time
# Set the GPIO port to input mode
GPIO.setmode(GPIO.BCM)
GPIO.setup(21, GPIO.IN)
# Monitor sensor data
def monitor_sensor():
# Read sensor value
sensor_value = GPIO.input(21)
# Determine whether to trigger an alarm based on the sensor value
if sensor_value == GPIO.LOW:
# Trigger an alarm
print("Alarm!")
else:
# Normal state
print("Normal.")
# Loop to execute sensor monitoring operations
while True:
monitor_sensor()
This sample code demonstrates the use of Python to implement a basic monitoring and alarm system. By continuously reading sensor data and determining whether to trigger an alarm based on the data, the system monitors the external environment.
5. Summary
This article introduced the basic principles and implementation of Python PLC and provided five example code examples demonstrating its application scenarios and specific implementation. As a simple and easy-to-learn programming method, Python PLC opens up new possibilities for the development and application of programmable logic controllers. With technological advancements and the growing demand for automated control, Python PLC is increasingly being used in industrial automation. It not only simplifies the complexity of PLC programming but also provides more flexible and powerful functionality.
However, Python PLC also presents some challenges and limitations. First, compared to traditional PLC programming languages, Python’s execution efficiency is lower, making it unsuitable for control tasks requiring high real-time performance. Second, using Python PLC requires knowledge of the Python language and related library functions, which can present a learning curve for engineers without a programming background.
In general, Python PLC, as a programmable logic controller, offers advantages such as ease of learning and high flexibility. It is suitable for scenarios with less demanding real-time requirements and more complex control logic. As Python’s application in industrial automation continues to deepen, I believe Python PLC will see wider application and development in the future.