The greenhouse environment control system is a core support for modern agricultural production. By utilizing Siemens PLC, it achieves intelligent interlinked adjustments of multiple parameters such as temperature, humidity, and light, significantly improving crop yield and quality while reducing labor management costs.
1. Hardware Configuration
PLC Selection
The Siemens S7-1200 series CPU 1214C DC/DC/DC model (14 points DI, 10 points DO, 2 channels AI) is selected, suitable for multi-parameter monitoring and control scenarios in small to medium-sized greenhouses.
Expansion Modules
- SM 1231 8AI module: Collects multiple analog signal inputs
- SM 1232 4AO module: Outputs multiple control signals
- CP 1242-7 GPRS module: Enables remote communication
- CM 1241 RS485 module: Connects to serial bus devices
I/O Point Table
| Address | Function Description | Signal Type |
|---|---|---|
| I0.0 | System Start Button | Digital Input |
| I0.1 | System Stop Button | Digital Input |
| I0.2 | Manual/Automatic Switch | Digital Input |
| I0.3 | Emergency Stop Switch | Digital Input |
| Q0.0 | Top Window Control | Digital Output |
| Q0.1 | Side Window Control | Digital Output |
| Q0.2 | Irrigation Pump Control | Digital Output |
| Q0.3 | Supplementary Light Control | Digital Output |
Analog Configuration
| Address | Function Description | Signal Type |
|---|---|---|
| AIW0 | Indoor Temperature | 4-20mA |
| AIW2 | Indoor Humidity | 4-20mA |
| AIW4 | Soil Moisture | 4-20mA |
| AIW6 | CO2 Concentration | 4-20mA |
| AQW0 | Fan Speed Control | 0-10V |
| AQW2 | Pump Flow Control | 0-10V |
Peripheral Devices
- PT100 Temperature and Humidity Sensor (Waterproof, ±0.2℃ accuracy)
- CO2 Concentration Transmitter (0-2000ppm range)
- Soil Moisture/EC/pH Three-in-One Sensor (with 485 interface)
- Illuminance Sensor (0-200000Lux range)
- Variable Frequency Fan and Pump (with ModBus communication interface)
Wiring Key Points
- Analog signals use shielded twisted pair cables, grounded at one end
- Remote sensors powered by a unified 24V supply, centralized distribution
- Actuator circuits configured with separate fuse protection
- Field bus devices use T-shaped topology wiring
2. Control Program Design
Variable Definition
1// Global Variable Definition (Simplified Version)
2VAR_GLOBAL
3 g_bSysRunning : BOOL; // System Running Status
4 g_rTempIn : REAL; // Indoor Temperature Value
5 g_rHumIn : REAL; // Indoor Humidity Value
6 g_rSoilMoist : REAL; // Soil Moisture Value
7 g_rCO2Level : REAL; // CO2 Concentration
8 g_rLightIntensity : REAL; // Light Intensity
9END_VAR
Program Architecture
The main program uses the organization block OB1 for periodic calls, divided into five functional blocks: data acquisition, parameter calculation, interlinked control, alarm processing, and remote communication. The temperature control uses a PID algorithm, and multi-target parameter optimization employs a weighted decision model.
PID Temperature Control Function Block
1// Temperature Control PID Function Block (Core Algorithm)
2"PID_Temp_Controller"(
3 Setpoint := "DB_Params".TempSetpoint,
4 Input := #g_rTempIn,
5 Input_PER := "AI_TempSignal",
6 Output := #TempControlOutput,
7 Cycle := t#100ms,
8 Gain := 1.8,
9 Ti := t#120s,
10 Td := t#30s,
11 MinOut := 0.0,
12 MaxOut := 100.0);
Multi-Parameter Interlinked Control Module
The design of the environmental factor interlinked control module handles the interactive effects between temperature, humidity, CO2, and light parameters. Based on the crop growth stage, it automatically switches different preset values for environmental parameters, achieving customized growth environment control. This module employs a two-layer decision logic: the first layer determines the growth stage, and the second layer determines the environmental parameter adjustment strategy.
Remote Communication and Data Storage
Data remote transmission is achieved through the CP 1242-7 GPRS module. Complete environmental parameters are collected every 10 minutes and stored in the DB300 data block, with data cyclically saved for 72 hours. Important parameter changes exceeding thresholds trigger immediate alarms. Remote operations are transmitted via secure protocol encryption, supporting hierarchical control based on authorization levels.
Fault Safety Strategy
A three-level fault safety strategy is designed: when a sensor fails, switch to a backup sensor or use interpolation algorithms; during communication interruptions, maintain the last valid control state; when the controller fails, automatically switch to a safe control mode (default to opening windows and shutting down high-energy-consuming devices).
1// Fault Safety Handling Code Snippet
2IF #SensorFailure THEN
3 IF #BackupSensorAvailable THEN
4 #ActualValue := #BackupSensorValue;
5 ELSE
6 #ActualValue := (#LastValidValue * 0.7) + (#PredictedValue * 0.3);
7 END_IF;
8 #AlarmStatus.SensorFailure := TRUE;
9END_IF;
3. User Interface
Main Screen Design
- Environmental Monitoring Main Screen: Real-time display of temperature, humidity, light, CO2 curves, supporting 1 hour/6 hours/24 hours switching
- Device Status Screen: Visualization of operational status and parameters for fans, pumps, shading curtains, etc.
- Parameter Setting Screen: Parameter configuration forms categorized by crop type and growth stage
- Alarm Record Screen: Historical alarm information and processing status tracking
Parameter Setting Function
- Environmental parameter template configuration for different crop types (can store standard parameters for 10 common crops)
- Day/Night parameter automatic switching settings (supports smooth transition algorithms)
- Emergency control strategy settings for special weather conditions
Remote Monitoring Function
- Mobile APP for real-time monitoring and alarm push
- Remote operation authorization management based on permissions
- Environmental data export and analysis function
- Remote diagnosis function for device status
4. System Debugging
Step-by-Step Debugging Method
- I/O Point Testing: Check digital/analog signal collection and output one by one
- Single Device Control Testing: Test the response of fans, pumps, curtains, etc. separately
- Closed-Loop Control Testing: Test the performance of closed-loop control for single parameters like temperature and humidity
- Interlinked Control Testing: Simulate multi-parameter changes to verify interlinked control strategies
- Communication Testing: Test the stability of local/remote communication
Parameter Tuning Key Points
- Initial PID parameter values set using the Z-N method, adjusted based on actual response
- Temperature and humidity interlinked control parameters should consider system time delay, appropriately increasing integral time
- Control parameters for summer and winter should be optimized separately and switched automatically
Abnormal Simulation Testing
- Sensor Fault Simulation: Disconnection, short circuit, signal drift
- Actuator Abnormal Simulation: Fan jamming, pump running dry
- Communication Interruption Simulation: GPRS signal loss, bus communication interruption
- Extreme Weather Simulation: High temperature, low temperature, heavy rain, etc. testing
5. Experience Summary
Common Issues and Solutions
- Temperature and humidity sensor accuracy drift after long-term use: Calibration every quarter
- Difficulty in CO2 control under high summer temperatures: Implement temperature-first, CO2-second control strategy
- Unstable remote communication: Add local data caching, automatically upload after communication recovery
- PID control parameters have poor seasonal adaptability: Implement adaptive parameter adjustment based on meteorological data
System Optimization Suggestions
- Increase meteorological data access to implement predictive control strategies
- Apply machine learning algorithms to optimize control parameters based on historical data
- Integrate water and fertilizer systems for more precise crop nutrient management
- Add edge computing capabilities to reduce the load on the central controller
Function Expansion Directions
- Integrate image recognition technology for monitoring crop growth status
- Add IoT platform for collaborative control of multiple greenhouses
- Combine big data analysis to optimize production cycles and energy utilization
- Introduce expert systems to provide precise environmental control strategies for different crops
The greenhouse environment control system achieves multi-parameter intelligent interlinked adjustments through Siemens PLC. The system configuration should be appropriately adjusted based on actual planting needs and scale. We welcome you to share your implementation experiences and improvement suggestions to collectively enhance the intelligence level of modern agricultural production.