Improving Incremental Nonlinear Dynamic Inversion Robustness Using Robust Control in Aerial Robotics

TL;DR

This paper presents a novel control architecture combining INDI with $ ext{H}_ extinfty$ controllers to significantly improve disturbance rejection in multirotor drones, validated through simulations and real-world experiments.

Contribution

It introduces a new cascaded control architecture that integrates INDI with structured $ ext{H}_ extinfty$ controllers for enhanced robustness in aerial robotics.

Findings

Over 50% improvement in disturbance rejection in simulations and experiments.

Effective control of multirotor drone dynamics under external disturbances.

Validated approach on both simulated and real quadcopter platforms.

Abstract

Improving robustness to uncertainty and rejection of external disturbances represents a significant challenge in aerial robotics. Nonlinear controllers based on Incremental Nonlinear Dynamic Inversion (INDI), known for their ability in estimating disturbances through measured-filtered data, have been notably used in such applications. Typically, these controllers comprise two cascaded loops: an inner loop employing nonlinear dynamic inversion and an outer loop generating the virtual control inputs via linear controllers. In this paper, a novel methodology is introduced, that combines the advantages of INDI with the robustness of linear structured $\mathcal{H}_\infty$ controllers. A full cascaded architecture is proposed to control the dynamics of a multirotor drone, covering both stabilization and guidance. In particular, low-order $\mathcal{H}_\infty$ controllers are designed for the outer loop by properly structuring the problem and solving it through non-smooth optimization. A comparative analysis is conducted between an existing INDI/PD approach and the proposed INDI/$\mathcal{H}_\infty$ strategy, showing a notable enhancement in the rejection of external disturbances. It is carried out first using MATLAB simulations involving a nonlinear model of a Parrot Bebop quadcopter drone, and then experimentally using a customized quadcopter built by the ENAC team. The results show an improvement of more than 50\% in the rejection of disturbances such as gusts.