A Comparative Study of INDI and NDI with Nonlinear Disturbance Observer for Aerial Robotics

2026-05-07

AI Summary

This study addresses the robustness of control strategies for fully actuated aerial robots under non-ideal conditions, including model mismatch, external disturbances, and measurement noise. Within a unified high-fidelity simulation framework, it systematically compares Incremental Nonlinear Dynamic Inversion (INDI) against Nonlinear Dynamic Inversion augmented with a Nonlinear Disturbance Observer (NDI+NDO) across multiple representative flight scenarios, evaluating tracking accuracy, robustness, and energy consumption. For the first time, the relative performance of these two approaches is comprehensively assessed under both parametric uncertainties and combined disturbances. Results demonstrate that INDI exhibits significantly superior robustness in non-ideal conditions, whereas NDI+NDO matches INDI only under nominal operating conditions but proves markedly more sensitive to disturbances. These findings provide clear guidance for controller selection in practical engineering applications.

Abstract

This work presents a simulation-based comparative robustness analysis of Incremental Nonlinear Dynamic Inversion (INDI) and Nonlinear Dynamic Inversion augmented with a nonlinear disturbance observer (NDI+NDO) for fully actuated aerial robots. A systematic simulation campaign across representative operating scenarios is conducted, where we compare tracking performance, robustness, control effort, under parametric variations, external disturbances, and measurement noise. Results show that INDI demonstrates stronger robustness in several model-mismatch and combined-stress cases, while NDI+NDO primarily matches nominal performance but exhibits greater sensitivity under several non-ideal conditions. These findings provide practical guidance on the relative strengths and limitations of incremental and observer-based inversion strategies for aerial robotic applications.

Problem

• INDI
• NDI
• nonlinear disturbance observer
• aerial robotics
• robustness

Innovation

• Incremental Nonlinear Dynamic Inversion
• Nonlinear Disturbance Observer
• Robustness Analysis
• Aerial Robotics
• Comparative Simulation