Linear Stability Analysis of an INDI Pitch-Rate Controller under Model Mismatch for a Tilt-Rotor VTOL UAV
This paper analyzes the linear stability of an INDI pitch-rate controller under model mismatch for a tilt-rotor VTOL UAV. A closed-form fifth-order transfer function is derived, and stability is characterized using the Routh-Hurwitz criterion. Two tuning procedures are proposed: robustness-oriented and performance-oriented. Control-effectiveness mismatch, especially sign errors, is identified as the most destabilizing factor.
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[Submitted on 17 Jul 2026]
Title:Linear Stability Analysis of an INDI Pitch-Rate Controller under Model Mismatch for a Tilt-Rotor VTOL UAV
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Abstract:Incremental Nonlinear Dynamic Inversion (INDI) is attractive for unmanned aerial vehicle (UAV) flight control because it reduces dependence on a full aerodynamic model while retaining strong disturbance-rejection capability. For a tilt-rotor vertical takeoff and landing (VTOL) architecture, however, the admissible model-mismatch range of the fast inner loop is still not characterized analytically in a parameter-explicit way. This paper isolates the pitch-rate/elevon subchannel of an existing cascaded INDI controller and studies its linear stability under model mismatch. A closed-form fifth-order transfer function is derived for the full controller-estimator-actuator-plant interconnection, and stability is characterized through the Routh-Hurwitz criterion over a parameterized linear model. Two representative three-parameter sweeps produce interpretable stability regions. Based on these feasibility maps, two uncertainty-aware tuning procedures are proposed: a robustness-oriented design that maximizes a weighted worst-case combination of gain margin and phase margin, and a performance-oriented design that maximizes worst-case closed-loop bandwidth subject to margin constraints. The results show that actuator lag and inertia mismatch are comparatively benign at nominal gain, whereas control-effectiveness mismatch, particularly a sign error in the allocation, is the most dangerous destabilizing factor, leading to concrete tuning recommendations for conservative and aggressive operating conditions.
Subjects:
Robotics (cs.RO)
Cite as: arXiv:2607.16471 [cs.RO]
(or arXiv:2607.16471v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2607.16471
arXiv-issued DOI via DataCite (pending registration)
Journal reference: Proceedings of the 10th International Conference on Control, Automation and Diagnosis (ICCAD), Lisbon, Portugal, 2026
Submission history
From: Lorenzo Schenk [view email] [v1] Fri, 17 Jul 2026 19:35:46 UTC (1,475 KB)
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