Robust Fault-tolerant Control for Quadcopter UAVs Using LMPC and INDI

This paper proposes a robust fault-tolerant control (FTC) framework (I-LMPC), for quadcopter unmanned aerial vehicles (UAVs) by integrating Linear Model Predictive Control (LMPC) with Incremental Nonlinear Dynamic Inversion (INDI). While the LMPC system constraints and generates optimal reference commands, its performance degrades under strong nonlinearities and model uncertainties. To address this limitation, a dual-loop architecture is introduced, where LMPC operates in the outer loop to provide optimal attitude and altitude references, and INDI functions in the inner loop to ensure high-frequency disturbance rejection and robustness against actuator faults. The approach is validated through MATLAB/Simulink simulations using a 6-DOF nonlinear quadcopter model. Results show that under a 40% loss of effectiveness (LOE) in a rotor, the proposed method maintains accurate trajectory tracking and stable attitude control, outperforming standalone LMPC and preventing system instability.

Authors

Publication Details

Journal
Journal of Institute of Control Robotics and Systems
Published
2026-05-11
DOI
https://doi.org/10.5302/j.icros.2026.26.0061
Primary Topic
Fault Detection and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
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article

Robust Fault-tolerant Control for Quadcopter UAVs Using LMPC and INDI

Seungkeun Kim, Jinyoung Suk, SeonWoo Kim, Donghoon Seo et al.
Journal of Institute of Control Robotics and Systems
Fault Detection and Control Systems
article

Robust Fault-tolerant Control for Quadcopter UAVs Using LMPC and INDI

Seungkeun Kim, Jinyoung Suk, SeonWoo Kim, Donghoon Seo, Taewon Yun
article en

Abstract

This paper proposes a robust fault-tolerant control (FTC) framework (I-LMPC), for quadcopter unmanned aerial vehicles (UAVs) by integrating Linear Model Predictive Control (LMPC) with Incremental Nonlinear Dynamic Inversion (INDI). While the LMPC system constraints and generates optimal reference commands, its performance degrades under strong nonlinearities and model uncertainties. To address this limitation, a dual-loop architecture is introduced, where LMPC operates in the outer loop to provide optimal attitude and altitude references, and INDI functions in the inner loop to ensure high-frequency disturbance rejection and robustness against actuator faults. The approach is validated through MATLAB/Simulink simulations using a 6-DOF nonlinear quadcopter model. Results show that under a 40% loss of effectiveness (LOE) in a rotor, the proposed method maintains accurate trajectory tracking and stable attitude control, outperforming standalone LMPC and preventing system instability.

Journal of Institute of Control Robotics and SystemsVol. 32(5)
Affordable and clean energy
Openalex Percentile: Top 7%
Fault Detection and Control Systems
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