Robust $\mathcal{H}_\infty$ Controller Design For INDI-Controlled Quadrotor Using Online Parameter Identification

TL;DR

This paper develops a robust, gain-scheduled $ ext{H}_ extinfty$ attitude controller for quadrotors that integrates online parameter identification within an INDI control framework, ensuring stability and performance under uncertainties.

Contribution

It introduces a novel gain-scheduled $ ext{H}_ extinfty$ controller for quadrotor attitude control that adapts based on online identified parameters, enhancing robustness.

Findings

The controller maintains stability margins under parameter uncertainties.

Flight tests show acceptable performance even with identified parameters outside initial uncertainty range.

Abstract

It has recently been shown that all physical parameters of an Incremental Nonlinear Dynamic Inversion (INDI) controller can be estimated onboard a multirotor within half a second, which is fast enough to do the full identification during a throw in the air. However, a robust method to tune outer loop gains for this feedback-linearizing INDI controller depending on the model parameters is still missing. This work presents the design of a robust gain-scheduled controller for attitude control of quadrotor, using an INDI-based inner loop with online identification of its system parameters. A gain-scheduled cascaded attitude controller with a feedforward filter is synthesized for a symmetric quadrotor using signal-based $\mathcal{H}_\infty$ closed-loop shaping. The resulting controller exhibits good stability margins, with nonlinear simulations confirming effective tracking performance under uncertainty. Experimental evaluation is also conducted through flight tests with full online parameter identification. Even though the identified parameters during these tests are far outside the defined uncertainty range, acceptable flight performance comparable to simulation results is maintained for actuator time constants below 40 ms.