cs.RONov 5, 2026

Fault-Geometry-Aware Control Allocation for Emergency Quadrotor Landing under Single-Motor Loss of Effectiveness

Authors: Suhas S P, Samridhi Salwan, Arshan Ali Khan, Ujwal Pai Jakarbet, Savithramma R M, Ashwini B P

Organizations: Department of CSE, Sidd ಮಾಗಾ Institute of Technology, Visvesvaraya Technological University, Tumakuru, Karnataka, India · Department of Economics, St. Joseph’s University, Bengaluru, Karnataka, India

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Abstract

Partial single-motor loss of effectiveness (LoE) changes the remaining control-authority geometry of a quadrotor and can change which control allocator performs best during emergency landing[cite: 11]. We compare three allocators in Crazyflie software-in-the-loop simulation: bounded weighted least squares (reported as PINV), a finite-candidate residual allocator (QP-lite), and the same residual allocator with scoring parameters tuned offline by the Cross-Entropy Method (CEM)[cite: 11]. For this study, fault geometry is represented by the known failed-motor index[cite: 11]. At η=0.496η=0.496 remaining effectiveness, matched development trials select CEM for M1, M3, and M4 and PINV for M2; the M3 selection is a one-trial margin (29/30 versus 28/30)[cite: 11]. After freezing this routing map, the policy achieves 117/120 safe first-contact touchdowns on fresh seeds and 115/120 in a separate randomized-order integrated-supervisor evaluation[cite: 11]. For the critical M2/PINV branch, Firth regression gives a nominal η50≈0.4956η_{50}\approx0.4956 with a within-model 95% bootstrap interval of approximately [0.4955, 0.4956][cite: 11]. One-factor-at-a-time ±10%\pm10\% plant perturbations shift η50η_{50} by up to 0.05495 for thrust coefficient and 0.04974 for mass; the most frequent violated first-contact criterion also changes from vertical speed in many conditions to angular rate for mass -10% and thrust-coefficient +10%[cite: 11]. At fixed η=0.496η=0.496, PINV has a higher M2 safe count than frozen CEM in 9/11 tested plant states and ties in 2/11; the two ties are both 0/30[cite: 11]. The experiments therefore distinguish motor-conditioned allocator selection from sensitivity to plant-model mismatch[cite: 11].

Figures & tables

Fig. 1: Implemented emergency-landing architecture. Nominal motor commands and supplied fault information (m,η)(m,\eta) enter the frozen supervisor before the simulated single-motor LoE block.
ExperimentConfigurationReplicationTrials
Complementarity4 motors ×\times 3 allocators, η=.496\eta=.49630 matched/motor360
Fresh holdoutfrozen routing30/motor120
Integrated supervisorfrozen routing, randomized order30/motor120
Nominal M2 boundary7 η\eta values30/ η\eta210
OFAT sensitivity10 plants ×\times 7 local η\eta30/ η\eta2100
M2 routing stability11 plants ×\times PINV/CEM30 paired660
TABLE I: Primary evaluation protocol. Development trials are separated from frozen-policy validation and robustness experiments. The total excludes offline CEM surrogate evaluations, exploratory/pilot runs, and the nonretained 120-trial supervisor-v2 follow-up.
Fig. 2: Matched development comparison at η=0.496\eta=0.496 (30 seeds per motor). The M3 CEM selection is 29/30 versus 28/30 for QP-lite.
Fig. 3: Per-motor fresh-holdout and integrated-supervisor results for the frozen routing map. Failed-motor identity is supplied to the supervisor.
Fig. 4: Nominal M2/PINV first-contact safety transition. Because η\eta is remaining effectiveness, lower η50\eta_{50} means tolerance to more severe LoE.
Fig. 5: M2/PINV η50\eta_{50} shifts for the ten ±10%\pm 10\% OFAT plant perturbations.
Fig. 6: Nonexclusive first-contact criterion-violation counts in the ten OFAT fine sweeps. Unannotated cells are zero.
Fig. 7: M2 safe-touchdown counts for PINV and frozen CEM at η=0.496\eta=0.496 . The two 0/30–0/30 ties are shown explicitly.
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