This page (revision-25) was last changed on 2021-11-08 09:09 by Murray Altheim

This page was created on 2019-12-22 08:01 by Murray Altheim

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PID Controller
PIDController

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At line 1 changed one line
It's surprisingly difficult to drive a wheeled robot in a straight line. No two motors have exactly the same performance, and there may also be differences in the floor surface. If we want a robot to follow a more complicated trajectory or to have some indication of where it has traveled, we need to be able to measure how far each wheel has traveled, that is, how many times the left and right wheels have rotated. This is called __[odometry]__.
It's surprisingly difficult to drive a wheeled robot in a straight line. No two motors have exactly the same performance, and there may also be differences in the floor surface. If we want a robot to follow a more complicated trajectory or to have some indication of where it has traveled, we need to be able to measure the distance each motor has traveled, that is, how many times the left and right wheels have rotated. This is called __[odometry]__.
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Besides the distance traveled, we also want to control the motors in such as way that the robot's movements are both accurate and smoothly executed. Regardless of whether the robot is traveling in a straight line, a gradual curve, or turning around, we want to set the left and right motors to operate at a specified speed and be able to accurately maintain that speed.
Besides the distance traveled, we also want to control the motors in such as way that the robot's movements are both accurate and smoothly executed. This means that regardless of whether the robot is traveling in a straight line, a gradual curve, or turning around, we want to set the left and right motors to operate at a specified speed and be able to accurately maintain that speed.
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On a typical robot with a motor on the left and a motor on the right side, to go forward one motor will be going clockwise, the other motor counter-clockwise. It's entirely typical of DC brushed motors to have a difference in performance in each direction, so it's entirely typical that such a robot will not run in a straight line. So having motor encoders and a PID controller is __exactly__ how one fixes this problem.
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See: [PID Rug Bump Challenge|PIDRugBumpChallenge], [Robot Chassis Dynamometer|RobotChassisDynamometer]
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|| Term || What It Does || Considerations
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|| Integral Term | integrates the error value into the correction over time so that it minimises this overshoot and pushes the output towards the target value. | the amount of integral applied to the formula needs to be carefully tuned, otherwise this can create its own form of oscillation. Given this tuning is quite tricky to get right, there is generally some overshoot and therefore oscillation in a PI controller. If the PID controller is used for position control the I term is used; for a motor controller the value is set to 0 since it actually represents the position of the motor if we're sampling at a fixed rate.
|| Derivative Term | projects the rate of change of the corrective value, and reduces its amount as the system nears the target. This allows the controller to move towards its Set Point as fast as possible, with as little oscillation as possible. | the Derivative Term is intended to smooth the operation of a PI Controller, but the value of the Derivative must also be tuned. If either the P or D are too high it can cause the system to oscillate.
|| Integral Term | integrates the error value into the correction over time so that it minimises this overshoot and pushes the output towards the target value. | the amount of integral applied to the formula needs to be carefully tuned, otherwise this can create its own form of oscillation. Given this tuning is quite tricky to get right, there is generally some overshoot and therefore oscillation in a PI controller.
|| Derivative Term | projects the rate of change of the corrective value, and reduces its amount as the system nears the target. This allows the controller to move towards its Set Point as fast as possible, with as little oscillation as possible. | the Derivative Term is intended to smooth the operation of a PI Controller, but the value of the Derivative must also be tuned.
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The more I read about PID controllers the more I found that tuning the control terms is considered something of a black art. There are a number of constants in the formula, and tweaking them is done by trial and error, in other words: guessing. I did
learn one rule of thumb for a PD controller: start at three zeros, then turn up the P until it oscillates, then back off to half that value. Then do the same thing with D.
The more I read about PID controllers the more I found that tuning the Integral and Derivative control terms is considered something of a black art. There are a number of constants in the formula, and tweaking them is done by trial and error, in other words: guessing.
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* __[PID Controller|https://en.wikipedia.org/wiki/PID_controller]__ from Wikipedia (note the animation of adjusting P,I,D values in the ''Manual tuning'' section)
* __[Improving the Beginner’s PID – Introduction|http://brettbeauregard.com/blog/2011/04/improving-the-beginners-pid-introduction/]__ by Brett Beauregard
* __[PID for Dummies|https://www.csimn.com/CSI_pages/PIDforDummies.html]__
* __[Going Straight with PID|https://projects.raspberrypi.org/en/projects/robotPID/3]__, from RaspberryPi.org
* [PID Autotune|https://platformio.org/lib/show/3/PID-AutoTune] by Brett Beauregard (C++)
* [Build a PID Controller with Python 2019|https://onion.io/2bt-pid-control-python/] from Onion.io
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* [simple-pid|https://pypi.org/project/simple-pid/] in Python
* [ivPID|https://github.com/ivmech/ivPID] in Python
* [PID controller|https://solderspot.wordpress.com/2014/01/29/pid-controllers-101/], blog post
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This page (revision-25) was last changed on 2021-11-08 09:09 by Murray AltheimTop