Menu
Going from a finished print to a great print takes a lot of calibration steps. Besides having the heatbed leveled correctly, and the extruder perfectly calibrated to melt just enough filament, the temperature of the hotend and the heatbed is just as important. Today i am going to show you how to perform a PID Tuning to have constant and accurate temperatures during your prints.
May 05, 2019 Run the M106 S255 command in order to set your cooling fan to 100%; Run the M303 E0 S215 C8 command and wait for the process to finish. The message “PID Autotune start” will appear in the terminal. Your hotend will start to gradually heat and get new readings. Now with the Keenovo heater installed there is no issue heating the bed to 85 degrees and beyond. It took a mere 124 secs to heat the bed from 17C to 85C. To achieve this impressive performance, the heater is powered by the AC mains voltage. However, the proximity of this AC current interferes with the operation of the EZABL sensor. Feb 15, 2015 PID tuning heatbed fail, 'timeout'. (Page 1) — Software & Firmware — SoliForum - 3D Printing Community —. Did you wait for the bed to come up to temp first before running autotune? If it waits too long to get up to temp it will time out. Heated Bed - Glass Plate - Auto Fire Extinguisher Ord Bot Hadron - RAMPS 1.4 - Bulldog. To tune the heated bed, use P1 (Repetier), E-1 (Marlin, others), or E1 (Smoothie). On multi-extruder machines, use the number of the extruder you want to tune (starting with 0). On multi-extruder machines, use the number of the extruder you want to tune (starting with 0). The heat manager can also be changed to use PID which can yield better results after running the PID Tuning command for a set temperature. (PID is a control loop feedback mechanism with many uses. A general description of PID is beyond the scope of this article. ) Tune the PID control system to the temperature you most frequently use. Tuning a bed heater may take more than half an hour, depending on the thermal capacity of the bed. You can cancel tuning by sending M0. After you have run auto tuning and checked that the heater control is working well, run M500 to save the heater parameters in config-override.g (this is.
What is PID Tuning?
Before starting with the guide on how to do a PID tuning, we fist need to understand the concept. In just a few words, PID is an algorithm that makes sure the heaters for both hotend and heatbed supply just enough heat in order to have the difference between the highest and lowest temperature as small as possible. If you are interested in learning more about what is PID, you can check this Wikipedia article where a PID controller is described
Prerequisites for 3D Printer PID Calibration
In order to perform a successful 3D printer PID tuning, you need to have the 3D printer connected to your computer via USB. Next, you need to access the terminal for your printer firmware. Today i will use Pronterface but anything will do, as long as you are able to send G-Code commands to the printer.
Hotend PID Tuning
Now that we have the 3D Printer connected to the computer, we can start the Hotend PID Calibration.
- Get the current PID settings using the
M503
command. Your printer will return the current PID settings. - Run the
M106 S255
command in order to set your cooling fan to 100% - Run the
M303 E0 S215 C8
command and wait for the process to finish.
The message “PID Autotune start” will appear in the terminal. Your hotend will start to gradually heat and get new readings.
Hotend PID Tuning Pronterface
While the hotend PID Calibration is underway, let’s understand the command we ran.
M303
– This command initiates a process of heating and cooling to determine the proper PID values for the specified hotend or the heated bed.E0
– This argument selects the extruder we want to calibrate. I have only one extruder, so i will set it to 0.S215
– This argument sets the temperature for the extruder PID Calibration to 215C.C8
– This argument sets the number of cycles we want to run. I selected 8 because it’s the recommended value in Marlin firmware, but any value from 3 to 10 is great.When the message “PID Autotune Finished” is displayed in the terminal window, the hotend PID Tuning is complete.
You will also see new Kp, Ki and Kd constants that need to be saved so let’s do that now. The previous values were so we need to adapt the command with the new values and save them.
- Run the
M301 P24.36 I1.39 D106.76
command to add the new values - Run
M500
to save the values. - Run
M503
to check your current values. These should be the same as the values we just saved.
Save new Hotend PID settings
Heatbed PID Tuning
If you managed to perform the hotend calibration, then the heatbed PID Calibration will be much easier.
- Get the current PID settings using the
M503
command. Your printer will return the current PID settings for the heatbed. - Run the
M303 E-1 S60 C8
command and wait for the process to finish.
The message “PID Autotune start” will appear in the terminal. Your heatbed will start to gradually heat and get new readings. While the heatbed PID calibration is underway, let’s understand the command we ran.
M303
– This command initiates a process of heating and cooling to determine the proper PID values for the specified hotend or the heated bed.E-1
– This argument selects the heatbed we want to calibrate. I have only one heatbed, so i will set it to 1.S60
– This argument sets the temperature for the heatbed PID Calibration to 60C.C8
– This argument sets the number of cycles we want to run. I selected 8 because it’s the recommended value in Marlin firmware, but any value from 3 to 10 is great.When the message “PID Autotune Finished” is displayed in the terminal window, the hotend PID Tuning is complete.
You will also see new Kp, Ki and Kd constants that need to be saved so let’s do that now. The previous values were so we need to adapt the command with the new values and save them.
- Run the
M304 P824.78 I154.89 D1097.99
command to add the new values - Run
M500
to save the values. - Run
M503
to check your current values. These should be the same as the values we just saved.
More information about PID Tuning can be found on the RepRap wiki
English • العربية • български • català • čeština • Deutsch • Ελληνικά • español • فارسی • français • hrvatski • magyar • italiano • română • 日本語 • 한국어 • lietuvių • Nederlands • norsk • polski • português • русский • Türkçe • українська • 中文(中国大陆) • 中文(台灣) • עברית • azərbaycanca • |
PID tuning refers to the parameters adjustment of a proportional-integral-derivative control algorithm used in most repraps for hot ends and heated beds.
PID needs to have a P, I and D value defined to control the nozzle temperature. If the temperature ramps up quickly and slows as it approaches the target temperature, or if it swings by a few degrees either side of the target temperature, then the values are incorrect.
To run PID Autotune in Marlin and other firmwares, run the following G-code with the nozzle cold:
This will heat the first nozzle (E0), and cycle around the target temperature 8 times (C8) at the given temperature (S200) and return values for P I and D. An example from http://www.soliwiki.com/PID_tuning is:
For Marlin, these values indicate the counts of the soft-PWM power control (0 to PID_MAX) for each element of the control equation. The softPWM value regulates the duty cycle of the f=(FCPU/16/64/256/2) control signal for the associated heater. The proportional (P) constant Kp is in counts/C, representing the change in the softPWM output per each degree of error. The integral (I) constant Ki in counts/(C*s) represents the change per each unit of time-integrated error. The derivative (D) constant Kd in counts/(C/s) represents the change in output expected due to the current rate of change of the temperature. In the above example, the autotune routine has determined that to control for a temperature of 200C, the soft PWM should be biased to 92 + 19.56*error + 0.71 * (sum of errors*time) -134.26 * dError/dT. The 'sum of errors*time' value is limited to the range +/-PID_INTEGRAL_DRIVE_MAX as set in Configuration.h. Commercial PID controllers typically use time-based parameters, Ti=Kp/Ki and Td=Kd/Kp, to specify the integral and derivative parameters. In the example above: Ti=19.56/0.71=27.54s, meaning an adjustment to compensate for integrated error over about 28 seconds; Td=134.26/19.56=6.86s, meaning an adjustment to compensate for the projected temperature about 7 seconds in the future.
The Kp, Ki, and Kd values can be entered with:
In the case of multiple extruders (E0, E1, E2) these PID values are shared between the extruders, although the extruders may be controlled separately. If the EEPROM is enabled, save with M500. If it is not enabled, save these settings in Configuration.h.
For the bed, use:
and save bed settings with:
For manual adjustments:
- if it overshoots a lot and oscillates, either the integral gain needs to be increased or all gains should be reduced
- Too much overshoot? Increase D, decrease P.
- Response too damped? Increase P.
- Ramps up quickly to a value below target temperature (0-160 fast) and then slows down as it approaches target (160-170 slow, 170-180 really slow, etc) temperature? Try increasing the I constant.
See also Wikipedia's PID_controller and Zeigler-Nichols tuning method. Marlin autotuning (2014-01-20, https://github.com/ErikZalm/Marlin/blob/Marlin_v1/Marlin/temperature.cpp#L250 ) uses the Ziegler-Nichols 'Classic' method, which first finds a gain which maximizes the oscillations around the setpoint, and uses the amplitude and period of these oscillations to set the proportional, integral, and derivative terms.
Saving PID settings
You will need to commit your changes to EEPROM or your configuration.h file for them to be permanent.
To save to EEPROM use:M500
Running Bed Heat Auto Tune Kit
Modifying Marlin Autotune parameters
The default Marlin M303 calculates a set of Ziegler-Nichols 'Classic' parameters based on the Ku (Ultimate Gain) and the Pu (Ultimate Period), where the Ku and Pu are determined by searching for a biased BANG-BANG oscillation around an average power level that produces oscillations centered on the setpoint. (See https://github.com/ErikZalm/Marlin/blob/Marlin_v1/Marlin/temperature.cpp#L238 )
You can transform these 'Classic' parameters into the Zeigler-Nichols 'Some Overshoot' set with:
Or the Z-N 'No Overshoot' set:
Note that the multipliers for the autotuning parameters each have only one significant digit (implying 10% maximum precision), and that the other schemes differ by factors of 2 or 3. PID autotuning and tuning isn't terribly precise, and changes in the parameters by factors of 5 to 50% are perfectly reasonable.
In Marlin, the parameters that control and limit the PID controller can have more significant effects than the popular PID parameters. For example, PID_MAX and PID_FUNCTIONAL_RANGE, and PID_INTEGRAL_DRIVE_MAX can each have dramatic, unexpected effects on PID behavior. For instance, a too-large PID_MAX on a high-power heater can make autotuning impossible; a too-small PID_FUNCTIONAL_RANGE can cause odd reset behavior; a too large PID_FUNCTIONAL_RANGE can guarantee overshoot; and a too-small PID_INTEGRAL_DRIVE_MAX can cause droop.
PID Tuning by Commercial PID
If you have access to a PID controller unit and a compatible thermal probe that fits down into your hotend, you can use them to tune your PID and calibrate your thermistor.
Connection of the output of the PID to your heater varies depending on your electronics. (I used a 1K2:4K7 voltage divider to drop the 22V output of the PID to 5V for my bread-boarded VNP4904)
After the PID is connected you can use it to measure the nozzle temperature and correlate it with the thermistor readings and resistances.
Conversion from the commercial PID values of kP in %fullscale, Ti in seconds, and Td in seconds is as follows:
As an example, a $30 MYPIN TD4-SNR 1/16 DIN PID temperature controller and $10 type-K probe can hold a particular Wildseyed hotend with a 6.8ohm resistor at 185.0C+/-0.1C using 12V with about a 43.7% duty cycle, or 0.437*12*12/6.8=9.25W. Invoking the autotuning on the controller produces these parameters: P=0.8%/C, I=27s, D=6.7s. Converting these to Marlin PID values:
Differences between the results can be caused by physical differences in the systems, (e.g: the thermocouple is closer to the heater than the thermistor,) or by different choices of autotuning parameters (e.g.: the MYPIN TD4 autotuning process is a proprietary black box, while Marlin uses Zeigler-Nichols 'Classic' method.)
The Temperature/resistance table below was developed by using the PID+thermocouple system to set temperatures on a sample hotend by controlling the heater while measuring the thermistor resistance. These values can be used with Nophead's http://hydraraptor.blogspot.com/2012/11/more-accurate-thermistor-tables.html or Marlin's https://github.com/ErikZalm/Marlin/blob/Marlin_v1/Marlin/createTemperatureLookupMarlin.py to create calibrated thermistor tables. The PID column collects the autotuning values produced by the PID controller for the indicated temperature. The kP,Ki,Kd lists the converted parameters.
Temp | DutyCycle | Thermistor R | Commercial PID | Kp,Ki,Kd |
---|---|---|---|---|
60.0 | 6.0 | 31630 | ||
100.0 | 15.7 | 10108 | 1.1%/C, 35.5s, 8.8s | 2.81, 0.08, 3.13 |
120.0 | 22.5 | 5802 | 1.0%/C, 32.0s, 8.0s | 2.55, 0.08, 3.14 |
135.0 | 26.5 | 3967 | ||
150.0 | 28.5 | 2840 | 1.2%/C, 29.0s, 7.2s | 3.06, 0.10, 2.35 |
170.0 | 34.0 | 1829 | ||
185.0 | 43.7 | 1347 | 0.8%/C, 27s, 6.7s | 2.04, 0.08, 3.28 |
190.0 | 45.9 | 1200 | 0.8%/C, 26s, 6.5s | 2.04, 0.08, 3.18 |
200.0 | 51.0 | 977 |
Retrieved from 'https://reprap.org/mediawiki/index.php?title=PID_Tuning&oldid=185897'