pith. sign in

arxiv: 2605.05339 · v1 · submitted 2026-05-06 · 💻 cs.RO · math.OC

Passive Fault Tolerance through Tension-to-Thrust Feed-Forward: Hybrid Input-to-State Stability for Decentralized Multi-UAV Slung-Load Transport under Abrupt Cable Severance

Pith reviewed 2026-05-08 16:14 UTC · model grok-4.3

classification 💻 cs.RO math.OC
keywords multi-UAVslung-load transportcable severancepassive fault toleranceinput-to-state stabilitydecentralized controltension feed-forwardhybrid systems
0
0 comments X p. Extension

The pith

Feeding each UAV's local cable tension straight into its thrust command creates a passive recovery mechanism for abrupt cable severance in decentralized slung-load transport.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper develops a decentralized controller for multiple UAVs carrying a slung payload that tolerates sudden cable breaks without fault detection or coordinated reconfiguration. Each vehicle adds its measured tension force directly to its altitude thrust while a surrounding PD, anti-swing, and projection cascade maintains local feasibility. This passive routing is supported by a conditional hybrid practical input-to-state stability certificate that chains slack-bounded taut-cable reduction, bounded Lyapunov jumps at severance, inter-fault decay, and per-cycle contraction with factor ρ less than one into an explicit recovery envelope. Five-vehicle multibody simulations with a 10 kg payload, Kelvin-Voigt cables, and wind disturbances confirm recovery within one pendulum period and low position error; disabling the tension feed-forward increases error by over 30 percent and sag by nearly four times.

Core claim

The architecture routes each vehicle's measured cable tension directly into its altitude thrust command as T_i^ff = T_i, surrounded by a proportional-derivative, anti-swing, and projection cascade. The central theoretical result is a conditional hybrid practical input-to-state-stability certificate composed of a slack-excursion-bounded taut-cable reduction, bounded post-severance Lyapunov jumps, inter-fault decay, and per-fault-cycle contraction ρ ∈ (0,1), yielding an explicit recovery envelope under actuator, slack, and dwell-time assumptions. Validation in multibody simulation with five vehicles, 10 kg payload, Kelvin-Voigt cables, and Dryden wind demonstrates 0.312-0.328 m RMSE and 76.1-

What carries the argument

The tension-to-thrust feed-forward identity T_i^{ff}=T_i that passively compensates for instantaneous load redistribution after cable severance inside the local decentralized cascade.

Load-bearing premise

The recovery envelope requires that actuator commands stay within limits, cable slack remains bounded, and sufficient dwell time separates successive faults.

What would settle it

A simulation or experiment in which, after a cable severance meeting the slack and dwell conditions, the payload tracking error exceeds the predicted envelope or fails to contract by the stated factor ρ per fault cycle would disprove the hybrid stability certificate.

Figures

Figures reproduced from arXiv: 2605.05339 by Hadi Hajieghrary, Paul Schmitt.

Figure 1
Figure 1. Figure 1: Cooperative transport configuration and fault model. Five quadrotors view at source ↗
Figure 2
Figure 2. Figure 2: Per-drone control cascade and extension injection points. Top framed panel: baseline continuous-time controller with outer-loop PD and anti-swing view at source ↗
Figure 3
Figure 3. Figure 3: V4 dual-fault scenario in analysis and in Drake. Left: time-coloured payload trajectory over view at source ↗
Figure 4
Figure 4. Figure 4: P2-B payload-mass-mismatch sweep. Altitude sag RMS versus view at source ↗
Figure 6
Figure 6. Figure 6: Fault-centered causal ablation on V4, FF-on (solid) vs FF-off (dashed, view at source ↗
Figure 7
Figure 7. Figure 7: Self-announcement causal chain for V4 fault 1, where drone 0 is view at source ↗
read the original abstract

Abrupt cable severance in multi-UAV slung-load transport redistributes load and changes the active constraint set, leaving limited time for fault diagnosis and reconfiguration. Existing controllers rely on coordinated force allocation, peer-state exchange, or fixed cable topology, and therefore lack a certified decentralized recovery mechanism for unannounced severance. We present a passive architecture that routes each vehicle's measured cable tension directly into its altitude thrust command, $T_i^{\mathrm{ff}}=T_i$, while a surrounding proportional-derivative, anti-swing, and projection cascade preserves local tracking feasibility. The main contribution is a conditional hybrid practical input-to-state-stability certificate that composes a slack-excursion-bounded taut-cable reduction, bounded post-severance Lyapunov jumps, inter-fault decay, and per-fault-cycle contraction $\rho \in (0,1)$ into an explicit recovery envelope under stated actuator, slack, and dwell assumptions. We validate the controller in Drake multibody simulation with five vehicles, a 10 kg payload, Kelvin-Voigt cables, Dryden wind, and single- and dual-severance schedules: the closed loop attains 0.312-0.328 m RMSE, 76.1-95.2 mm peak sag, and recovery within one payload-pendulum period. Disabling the identity inflates cruise error by 34-39% and peak sag by 3.6x-4.0x, identifying local tension feed-forward as the dominant passive recovery mechanism in the tested decentralized cascade.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper introduces a passive fault-tolerant control architecture for decentralized multi-UAV slung-load transport that incorporates tension-to-thrust feed-forward (T_i^{ff} = T_i) to handle abrupt cable severances without requiring fault detection or reconfiguration. It establishes a conditional hybrid practical input-to-state stability (ISS) certificate by composing a slack-excursion-bounded reduction to the taut-cable dynamics, bounded Lyapunov function jumps at severance events, exponential decay between faults, and a per-cycle contraction factor ρ ∈ (0,1), resulting in an explicit recovery envelope under assumptions on actuator saturation, cable slack, and minimum dwell time. The approach is validated through Drake multibody simulations involving five UAVs carrying a 10 kg payload under Kelvin-Voigt cable models and Dryden wind disturbances, demonstrating RMSE values of 0.312-0.328 m, peak sags of 76.1-95.2 mm, and recovery within one payload-pendulum period for single- and dual-severance cases, with notable performance degradation when the feed-forward term is disabled.

Significance. If the stability certificate holds under the stated assumptions, this work offers a significant advance in passive, decentralized fault tolerance for aerial transportation systems, addressing a critical gap in handling unannounced topology changes without inter-vehicle communication. The explicit composition of the hybrid ISS components and the provision of quantitative recovery bounds represent a strength, particularly when combined with the simulation results that quantify the benefit of the tension feed-forward (34-39% RMSE increase and 3.6-4.0x sag increase without it). This could inform practical designs for robust multi-UAV operations in uncertain environments.

major comments (2)
  1. [Hybrid ISS Certificate] In the hybrid practical ISS certificate (the composition of slack-bounded reduction, jumps, decay, and contraction): the per-cycle contraction factor ρ ∈ (0,1) must be selected to satisfy the inequality and is listed among free parameters. The manuscript should provide either an explicit a priori computation of ρ from actuator limits, slack bounds, and dwell time or a clear statement that the envelope is conditional on such a choice being feasible, to ensure the recovery prediction is not reduced to a post-selection fit.
  2. [Lyapunov Analysis] In the Lyapunov analysis underlying the taut-cable reduction and post-severance jumps: explicit expressions for the Lyapunov functions and the quantitative bounds on the jumps at severance instants are referenced as part of the certificate but are not instantiated with the system parameters in the derivation. This makes independent verification of the bounded-jump and decay claims difficult.
minor comments (2)
  1. [Simulation Results] The simulation section reports that closed-loop metrics remain inside the predicted bounds, but the numerical values of those bounds (derived from the envelope) are not tabulated or stated alongside the 0.312-0.328 m RMSE and 76.1-95.2 mm sag figures.
  2. [Abstract and Validation] The abstract and validation paragraph use 'one payload-pendulum period' for recovery time; an explicit numerical value or formula for this period based on the 10 kg payload and cable parameters would improve clarity.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the positive evaluation and the recommendation of minor revision. The comments correctly identify opportunities to strengthen the presentation of the conditional hybrid practical ISS certificate. We address each point below and will incorporate the suggested clarifications.

read point-by-point responses
  1. Referee: In the hybrid practical ISS certificate (the composition of slack-bounded reduction, jumps, decay, and contraction): the per-cycle contraction factor ρ ∈ (0,1) must be selected to satisfy the inequality and is listed among free parameters. The manuscript should provide either an explicit a priori computation of ρ from actuator limits, slack bounds, and dwell time or a clear statement that the envelope is conditional on such a choice being feasible, to ensure the recovery prediction is not reduced to a post-selection fit.

    Authors: We agree that the dependence on ρ requires explicit qualification. The certificate is formulated as conditional on the existence of a feasible ρ ∈ (0,1) satisfying the per-cycle contraction inequality under the stated actuator saturation, slack-excursion, and minimum-dwell-time assumptions. In the revised manuscript we will insert a dedicated remark immediately following the statement of the main theorem (and again in the recovery-envelope discussion) that all quantitative bounds hold only when such a ρ can be chosen; we do not provide a closed-form a priori expression for ρ because it arises from the composition of the hybrid jump and flow maps and is therefore inherently parameter-dependent. This preserves the conditional character of the result and prevents any appearance of post-hoc fitting. revision: yes

  2. Referee: In the Lyapunov analysis underlying the taut-cable reduction and post-severance jumps: explicit expressions for the Lyapunov functions and the quantitative bounds on the jumps at severance instants are referenced as part of the certificate but are not instantiated with the system parameters in the derivation. This makes independent verification of the bounded-jump and decay claims difficult.

    Authors: We acknowledge that the main-text presentation keeps the Lyapunov functions and jump bounds in general form for readability, with full derivations placed in the supplementary material. To enable direct verification, the revised manuscript will expand the Lyapunov section to include the explicit quadratic forms V = x^T P x for the taut-cable error coordinates together with the concrete upper bounds on the jump map (ΔV ≤ γ ||x||^2) expressed in terms of cable stiffness, payload mass, and actuator saturation limits. The numerical value of the jump bound γ obtained from the simulation parameters will also be stated explicitly. These additions will make the bounded-jump and exponential-decay claims verifiable from the main text. revision: yes

Circularity Check

0 steps flagged

No significant circularity; derivation is self-contained composition under explicit assumptions

full rationale

The paper derives the hybrid practical ISS certificate by composing four explicitly stated pieces (slack-excursion-bounded taut-cable reduction, bounded post-severance Lyapunov jumps, inter-fault exponential decay, and per-cycle contraction) under actuator saturation, slack bounds, and minimum dwell-time assumptions. The contraction factor ρ ∈ (0,1) is shown to exist from these bounds rather than being fitted to data or defined circularly; simulation trajectories are reported only as validation that closed-loop metrics remain inside the analytically predicted envelope. No step reduces by construction to its own inputs, no self-citation is load-bearing for the central claim, and the manuscript is self-contained against the stated assumptions without renaming known results or smuggling ansatzes.

Axiom & Free-Parameter Ledger

1 free parameters · 2 axioms · 0 invented entities

The central claim rests on standard hybrid dynamical systems theory together with domain-specific bounds on actuator effort, cable slack, and inter-fault timing; no new physical entities are postulated.

free parameters (1)
  • contraction factor ρ = in (0,1)
    Selected inside (0,1) to enforce per-fault-cycle contraction in the stability envelope; its value is not derived from first principles but chosen to close the proof.
axioms (2)
  • standard math Hybrid input-to-state stability theory for systems with jumps
    Invoked to compose the taut-cable reduction, Lyapunov jump bounds, inter-fault decay, and contraction into a single recovery envelope.
  • domain assumption Actuator saturation limits, cable slack excursion bounds, and positive minimum dwell time between severances
    Required for the explicit recovery envelope to remain valid; stated in the abstract as necessary assumptions.

pith-pipeline@v0.9.0 · 5593 in / 1647 out tokens · 61946 ms · 2026-05-08T16:14:23.068701+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

25 extracted references

  1. [1]

    Cooperative manipulation and transportation with aerial robots,

    N. Michael, J. Fink, and V . Kumar, “Cooperative manipulation and transportation with aerial robots,”Autonomous Robots, vol. 30, no. 1, pp. 73–86, 2011. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY 16

  2. [2]

    Planning and control for cooperative manipulation and transportation with aerial robots,

    J. Fink, N. Michael, S. Kim, and V . Kumar, “Planning and control for cooperative manipulation and transportation with aerial robots,”The International Journal of Robotics Research, vol. 30, no. 3, pp. 324–334, 2011

  3. [3]

    Robust collaborative object transportation using multiple MA Vs,

    A. Tagliabue, M. Kamel, R. Siegwart, and J. Nieto, “Robust collaborative object transportation using multiple MA Vs,”The International Journal of Robotics Research, vol. 38, no. 9, pp. 1020–1044, 2019

  4. [4]

    Distributed model predictive control of linear discrete-time systems with local and global constraints,

    Z. Wang and C. J. Ong, “Distributed model predictive control of linear discrete-time systems with local and global constraints,”Automatica, vol. 81, pp. 184–195, Jul. 2017

  5. [5]

    Nonlinear model predictive control for cooper- ative transportation and manipulation of cable suspended payloads with multiple quadrotors,

    G. Li and G. Loianno, “Nonlinear model predictive control for cooper- ative transportation and manipulation of cable suspended payloads with multiple quadrotors,” in2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, Oct. 2023

  6. [6]

    Optimal trajectory planning for cooperative manipulation with multiple quadrotors using control barrier functions,

    A. Pallar, G. Li, M. Sarvaiya, and G. Loianno, “Optimal trajectory planning for cooperative manipulation with multiple quadrotors using control barrier functions,” in2025 IEEE International Conference on Robotics and Automation (ICRA). IEEE, May 2025

  7. [7]

    A robust adaptive formation control methodology for networked multi-UA V systems with appli- cations to cooperative payload transportation,

    Y .-H. Su, P. Bhowmick, and A. Lanzon, “A robust adaptive formation control methodology for networked multi-UA V systems with appli- cations to cooperative payload transportation,”Control Engineering Practice, Sep. 2023

  8. [8]

    Geometric tracking control of a quadrotor UA V on SE(3),

    T. Lee, M. Leok, and N. H. McClamroch, “Geometric tracking control of a quadrotor UA V on SE(3),” in49th IEEE Conference on Decision and Control (CDC). Atlanta, GA, USA: IEEE, 2010, pp. 5420–5425

  9. [9]

    Trajectory generation and control of a quadrotor with a cable-suspended load — A differentially- flat hybrid system,

    K. Sreenath, N. Michael, and V . Kumar, “Trajectory generation and control of a quadrotor with a cable-suspended load — A differentially- flat hybrid system,” in2013 IEEE International Conference on Robotics and Automation (ICRA). Karlsruhe, Germany: IEEE, 2013, pp. 4888– 4895

  10. [10]

    Geometric control of quadrotor UA Vs transporting a cable- suspended rigid body,

    T. Lee, “Geometric control of quadrotor UA Vs transporting a cable- suspended rigid body,”IEEE Transactions on Control Systems Technol- ogy, vol. 26, no. 1, pp. 255–264, Jan. 2018

  11. [11]

    Geometric control of cooperating multiple quadrotor UA Vs with a suspended payload,

    T. Lee, K. Sreenath, and V . Kumar, “Geometric control of cooperating multiple quadrotor UA Vs with a suspended payload,” in52nd IEEE Conference on Decision and Control (CDC). Firenze, Italy: IEEE, 2013, pp. 5510–5515

  12. [12]

    A geometric control approach for multi- UA V cooperative payload transfer,

    M. Sharma and S. Sundaram, “A geometric control approach for multi- UA V cooperative payload transfer,”Nonlinear Dynamics, Jun. 2023

  13. [13]

    Design and analysis of a novel L1 adaptive control architecture with guaranteed transient performance,

    C. Cao and N. Hovakimyan, “Design and analysis of a novel L1 adaptive control architecture with guaranteed transient performance,” IEEE Transactions on Automatic Control, vol. 53, no. 2, pp. 586–591, Mar. 2008

  14. [14]

    Hovakimyan and C

    N. Hovakimyan and C. Cao,L1 Adaptive Control Theory: Guaranteed Robustness with Fast Adaptation, ser. Advances in Design and Control. Philadelphia, PA, USA: SIAM, 2010

  15. [15]

    L 1quad:L 1 adaptive augmentation of geometric control for agile quadrotors with performance guarantees,

    Z. Wu, S. Cheng, P. Zhao, A. Gahlawat, K. A. Ackerman, A. Lak- shmanan, C. Yang, J. Yu, and N. Hovakimyan, “L 1quad:L 1 adaptive augmentation of geometric control for agile quadrotors with performance guarantees,”IEEE Transactions on Control Systems Technology, Mar. 2025

  16. [16]

    Blanke, M

    M. Blanke, M. Kinnaert, J. Lunze, and M. Staroswiecki,Diagnosis and Fault-Tolerant Control, 3rd ed. Berlin, Heidelberg, Germany: Springer, 2015

  17. [17]

    Bibliographical review on reconfigurable fault- tolerant control systems,

    Y . Zhang and J. Jiang, “Bibliographical review on reconfigurable fault- tolerant control systems,”Annual Reviews in Control, vol. 32, no. 2, pp. 229–252, 2008

  18. [18]

    Fault-tolerant control: The 1997 situation,

    R. J. Patton, “Fault-tolerant control: The 1997 situation,” inIFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS’97). Hull, United Kingdom: IFAC, Aug. 1997, pp. 1033–1055, plenary survey

  19. [19]

    Fault-tolerant control for the multi-quadrotors cooperative transportation under suspension failures,

    X. Liang, Z. Su, W. Zhou, G. Meng, and L. Zhu, “Fault-tolerant control for the multi-quadrotors cooperative transportation under suspension failures,”Aerospace Science and Technology, vol. 119, p. 107139, 2021

  20. [20]

    Cooperative transportation of drones without inter-agent communication,

    P.-X. Wu, H.-A. Hung, C.-C. Yang, and T.-H. Cheng, “Cooperative transportation of drones without inter-agent communication,” in2020 American Control Conference (ACC), July 2020, pp. 677–682

  21. [21]

    From specification to certification: Torq-ordered rulebooks and robust hocbf optimization for safe autonomous driving,

    H. Hajieghrary, B. Walter, and P. Schmitt, “From specification to certification: Torq-ordered rulebooks and robust hocbf optimization for safe autonomous driving,” in2026 IEEE/SICE International Symposium on System Integration (SII), 2026, pp. 881–886

  22. [22]

    Goebel, R

    R. Goebel, R. G. Sanfelice, and A. R. Teel,Hybrid Dynamical Systems: Modeling, Stability, and Robustness. Princeton, NJ, USA: Princeton University Press, 2012

  23. [23]

    OSQP: an operator splitting solver for quadratic programs,

    B. Stellato, G. Banjac, P. Goulart, A. Bemporad, and S. Boyd, “OSQP: an operator splitting solver for quadratic programs,”Mathematical Programming Computation, vol. 12, no. 4, pp. 637–672, 2020

  24. [24]

    Drake: Model- based design and verification for robotics,

    Tedrake, Russ and the Drake Development Team, “Drake: Model- based design and verification for robotics,” 2019. [Online]. Available: https://drake.mit.edu

  25. [25]

    Col- laborative transportation using mavs via passive force control,

    A. Tagliabue, M. Kamel, S. Verling, R. Siegwart, and J. Nieto, “Col- laborative transportation using mavs via passive force control,” in2017 IEEE International Conference on Robotics and Automation (ICRA), May 2017, pp. 5766–5773