PID Climate¶
The pid
climate platform allows you to regulate a value with a
PID controller.
PID controllers are good at modulating an output signal to get a sensor reading to a specified setpoint. For example, it can be used to modulate the power of a heating unit to get the temperature to a user-specified setpoint.
Explaining how PID controllers work in detail is out of scope of this documentation entry, but there’s a nice article explaining the function principle here.
# Example configuration entry
climate:
- platform: pid
name: "PID Climate Controller"
sensor: temperature_sensor
default_target_temperature: 21°C
heat_output: heater
control_parameters:
kp: 0.49460
ki: 0.00487
kd: 12.56301
Configuration variables:¶
sensor (Required, ID): The sensor that is used to measure the current temperature.
default_target_temperature (Required, float): The default target temperature (setpoint) for the control algorithm. This can be dynamically set in the frontend later.
heat_output (Optional, ID): The ID of a float output that increases the current temperature. At least one of
heat_output
andcool_output
must be specified.cool_output (Optional, ID): The ID of a float output that decreases the current temperature. At least one of
heat_output
andcool_output
must be specified.control_parameters (Required): Control parameters of the PID controller.
kp (Required, float): The factor for the proportional term of the PID controller.
ki (Optional, float): The factor for the integral term of the PID controller. Defaults to
0
.kd (Optional, float): The factor for the derivative term of the PID controller. Defaults to
0
.min_integral (Optional, float): The maximum value of the integral term multiplied by
ki
to prevent windup. Defaults to-1
.max_integral (Optional, float): The minimum value of the integral term multiplied by
ki
to prevent windup. Defaults to1
.
All other options from Climate.
PID Controller Setup¶
To set up a PID climate controller, you need a couple of components:
A Sensor to read the current temperature (
sensor
).At least one float output to drive for heating or cooling (or both). This could for example be a PWM output via Slow PWM Output that drives a heating unit.
Please note the output must be controllable with continuous value (not only ON/OFF, but any state in between for example 50% heating power).
Note
The sensor should have a short update interval. The PID update frequency is tied to the update
interval of the sensor. Set a short update_interval
like 1s
on the sensor.
Autotuning¶
Finding suitable kp
, ki
and kd
control parameters for the PID controller manually
needs some experience with PID controllers. ESPHome has an auto-tuning algorithm that automatically
finds suitable PID parameters to start using an adaption of the Ziegler-Nichols method with
relay autotuning (Åström and Hägglund).
To autotune the control parameters:
Set up the PID controller with all control parameters set to zero:
climate: - platform: pid id: pid_climate name: "PID Climate Controller" sensor: temperature_sensor default_target_temperature: 21°C heat_output: heater control_parameters: kp: 0.0 ki: 0.0 kd: 0.0
Create a template switch to start autotuning later:
switch: - platform: template name: "PID Climate Autotune" turn_on_action: - climate.pid.autotune: pid_climate
Compile & Upload the new firmware.
Now you should have a climate entity called “PID Climate Controller” and a switch called “PID Climate Autotune” visible in your frontend of choice.
The autotune algorithm works by repeatedly switching the heat/cool output to full power and off. This induced an oscillation of the observed temperature and the measured period and amplitude is automatically calculated.
But this also means you have to set the setpoint of the climate controller to a value the device can reach. For example if the temperature of a room is to be controlled, the setpoint needs to be above the ambient temperature. If the ambient temperature is 20°C, the setpoint of the climate device should be set to at least ~24°C so that an oscillation can be induced.
Set an appropriate setpoint (see above).
Click on the “PID Climate Autotune” and view the logs of the device.
You should see output like
PID Autotune: Autotune is still running! Status: Trying to reach 24.25 °C Stats so far: Phases: 4 Detected 5 zero-crossings # ... For example, in the output above, the autotuner is driving the heating output at 100% and trying to reach 24.25 °C. This will continue for some time until data for 6 phases (or a bit more, depending on the data quality) have been acquired.
When the PID autotuner has succeeded, output like the one below can be seen:
PID Autotune: State: Succeeded! All checks passed! Calculated PID parameters ("Ziegler-Nichols PID" rule): Calculated PID parameters ("Ziegler-Nichols PID" rule): control_parameters: kp: 0.49460 ki: 0.00487 kd: 12.56301 Please copy these values into your YAML configuration! They will reset on the next reboot. # ...
Copy the values in
control_parameters
into your configuration.climate: - platform: pid # ... control_parameters: kp: 0.49460 ki: 0.00487 kd: 12.56301
Complete, compile & upload the updated firmware.
If the calculated PID parameters are not good, you can try some of the alternative parameters printed below the main control parameters in the log output.
climate.pid.autotune
Action¶
This action starts the autotune process of the PID controller.
on_...:
# Basic
- climate.pid.autotune: pid_climate
# Advanced
- climate.pid.autotune:
id: pid_climate
noiseband: 0.25
positive_output: 25%
negative_output: -25%
Configuration variables:
id (Required, ID): ID of the PID Climate to start autotuning for.
noiseband (Optional, float): The noiseband of the process (=sensor) variable. The value of the PID controller must be able to reach this value. Defaults to
0.25
.positive_output (Optional, float): The positive output power to drive the heat output at. Defaults to
1.0
.negative_output (Optional, float): The positive output power to drive the cool output at. Defaults to
-1.0
.
climate.pid.set_control_parameters
Action¶
This action sets new values for the control parameters of the PID controller. This can be used to manually tune the PID controller. Make sure to take update the values you want on the YAML file! They will reset on the next reboot.
on_...:
- climate.pid.set_control_parameters:
id: pid_climate
kp: 0.0
ki: 0.0
kd: 0.0
Configuration variables:
id (Required, ID): ID of the PID Climate to start autotuning for.
kp (Required, float): The factor for the proportional term of the PID controller.
ki (Optional, float): The factor for the integral term of the PID controller. Defaults to
0
.kd (Optional, float): The factor for the derivative term of the PID controller. Defaults to
0
.
climate.pid.reset_integral_term
Action¶
This action resets the integral term of the PID controller to 0. This might be necessary under certain conditions to avoid the control loop to overshoot (or undershoot) a target.
on_...:
# Basic
- climate.pid.reset_integral_term: pid_climate
Configuration variables:
id (Required, ID): ID of the PID Climate being reset.
pid
Sensor¶
Additionally, the PID climate platform provides an optional sensor platform to monitor the calculated PID parameters to help finding good PID values.
sensor:
- platform: pid
name: "PID Climate Result"
type: RESULT
Configuration variables:
name (Required, string): The name of the sensor
type (Required, string): The value to monitor. One of
RESULT
- The resulting value (sum of P, I, and D terms).ERROR
- The calculated error (setpoint - process_variable)PROPORTIONAL
- The proportional term of the PID controller.INTEGRAL
- The integral term of the PID controller.DERIVATIVE
- The derivative term of the PID controller.HEAT
- The resulting heating power to the supplied to theheat_output
.COOL
- The resulting cooling power to the supplied to thecool_output
.KP
- The current factor for the proportional term of the PID controller.KI
- The current factor for the integral term of the PID controller.KD
- The current factor for the differential term of the PID controller.
Advanced options:
climate_id (Optional, ID): The ID of the pid climate to get the values from.
See Also¶
Ziegler-Nichols Method: Nichols, N. B. and J. G. Ziegler (1942), ‘Optimum settings for automatic controllers’, Transactions of the ASME, 64, 759-768
Åström, K. J. and T. Hägglund (1984a), ‘Automatic tuning of simple regulators’, Proceedings of IFAC 9th World Congress, Budapest, 1867-1872