px4_pid_tuner

Python script for system identification and tuning of PX4 PID loops based on PX4 logs (ulog only).

It currently tunes the attitude rate loops only, ROLL_RATE_P/I/D gains. Similarly, for pitch/yaw. Future updates will allow attitude loop P gain tuning as well as translational velocity and position loops.

Background

The python script performs two main tasks.

1. Identifies a 2nd order system which will be used for PID tuning. This is done using SIPPY package.
2. Given the model identified in 1, it performs LQR-based PID tuning as described in this paper. In LQR-based tuning, the PID gains are optimal given specific LQR weight matrices, Q and R. To find best Q and R matrices, genetic optimization is employed using DEAP python package

Installation

Look at the required modules in the install.sh file.

Usage

The script is called from the command line with positional arguments as follows.

• To only show input/output data for inspection before identification, you can use the -sd true or --showDataOnly true argument.

python3 px4_pid_tuner.py -f log.ulg -sd true

• To select which axis i.e. roll/pitch/yaw, use the -a or --axis

python3 px4_pid_tuner.py -f log.ulg -a roll -sd true

If not provided, the default is roll

• To select data range (start/end time in seconds), use the -s for start and -e for end times. The time is in seconds

python3 px4_pid_tuner.py -f log.ulg -s 2.0 -e 5.5 -sd true

• If -sd true is not set, system identificaion and PID tuning will be performed. In addition, the data will be divided into mini-batches to find a data range with best-fit model. To disable the automatic data range selection, set autoSelect -as false and provide range of data manually using -s <start_time> and -e <end_time>. For example,

python3 px4_pid_tuner.py -f log.ulg -as false -s 2.0 -e 5.5

• If you want the script to try to automatically select data range with best fit, set -as true and determine the batch size using -bs 4.0 (4 seconds in this case).

python3 px4_pid_tuner.py -f log.ulg -as true -bs 4.0

• To determine the resampling time of i/o data, use -dt 0.001. Sampling time is in seconds.

python3 px4_pid_tuner.py -f log.ulg -as false -s 2.0 -e 5.5 -ddt 0.001

Notes

• The quality of system identification is highly dependent on the input/output data coming from the ulg file. If the system has poor data i.e. no excitation in different axes with different frequencies, the model can be off and PID tuning results will be useless.
• Make sure that you use the good portions of your data (ones with enough excitation), and one where the controller is active (outputing signal).
• The automatics data range selector (-as true) is not yet optimized, so, use common sense to judge if the resulting batch of the automatic range selector is really good portion of the data.

TODO

• Do more data pre-procssing to get better identified system.
• Implement a function similar to MATLAB function advice() (https://www.mathworks.com/help/ident/ref/advice.html). This will help to automatically analyze I/O data and provide recommendations for better model identification.
• Allow user to graphically select range of data from a plot for system identification
• Implement online optimal PID tuning !