An Adaptive PID Autotuner for Multicopters with Experimental Results

TL;DR

This paper introduces an adaptive PID autotuner for multicopters that optimizes autopilot performance during a single flight, demonstrating superior results over default settings through experimental validation.

Contribution

The paper presents a novel adaptive PID autotuner integrated into the PX4 flight stack, capable of real-time optimization during flight, with experimental validation on multicopters.

Findings

Autotuned autopilot outperforms default in flight tests.

Performance improvement observed across varying quadcopter masses.

Autotuner effectively adapts control parameters during a single flight.

Abstract

This paper develops an adaptive PID autotuner for multicopters, and presents simulation and experimental results. The autotuner consists of adaptive digital control laws based on retrospective cost adaptive control implemented in the PX4 flight stack. A learning trajectory is used to optimize the autopilot during a single flight. The autotuned autopilot is then compared with the default PX4 autopilot by flying a test trajectory constructed using the second-order Hilbert curve. In order to investigate the sensitivity of the autotuner to the quadcopter dynamics, the mass of the quadcopter is varied, and the performance of the autotuned and default autopilot is compared. It is observed that the autotuned autopilot outperforms the default autopilot.