# System Identification and $H_\infty$-based Control of Quadrotor Attitude

## TL;DR

This paper develops an $H_
abla$ control approach for quadrotor attitude stabilization, using system identification to handle uncertainties and demonstrating improved robustness and tracking performance over traditional controllers through real experiments.

## Contribution

It introduces a novel $H_
abla$ control method based on system identification for quadrotors, enhancing robustness against uncertainties.

## Key findings

- The $H_
abla$ controller outperforms PID and $mbda$ controllers in robustness.
- Experimental results confirm improved tracking accuracy.
- The approach effectively manages unmodelled dynamics and parameter uncertainties.

## Abstract

The attitude control of a quadrotor is a fundamental problem, which has a pivotal role in a quadrotor stabilization and control. What makes this problem more challenging is the presence of uncertainty such as unmodelled dynamics and unknown parameters. In this paper, to cope with uncertainty, an $H_\infty$ control approach is adopted for a real quadrotor. To achieve $H_\infty$ controller, first a continuous-time system identification is performed on the experimental data to encapsulate a nominal model of the system as well as a multiplicative uncertainty. By this means, $H_\infty$ controllers for both roll and pitch angles are synthesized. To verify the effectiveness of the proposed controllers, some real experiments and simulations are carried out. Results verify that the designed controller does retain robust stability, and provide a better tracking performance in comparison with a well-tuned PID and a $\mu$ synthesis controller.