Nonlinear Predictive Control of the Continuum and Hybrid Dynamics of a Suspended Deformable Cable for Aerial Pick and Place

2026-02-19

AI Summary

This study addresses the control challenges arising from continuum dynamics and hybrid events—such as payload attachment and detachment—in aerial manipulation tasks involving a drone carrying a retractable flexible cable. To this end, the authors develop a high-fidelity model based on partial differential equations, which is subsequently discretized via finite differences and reduced using Proper Orthogonal Decomposition (POD) to yield a low-dimensional reduced-order model (ROM). For the first time, this ROM is integrated with nonlinear model predictive control (NMPC) to enable real-time stabilization of the cable’s complex dynamics. Simulations demonstrate that the proposed approach effectively suppresses cable oscillations across diverse operating conditions, achieving an optimal balance between modeling accuracy and computational efficiency. Furthermore, it successfully enables trajectory planning in confined environments, exhibiting strong robustness and practical applicability.

Technology Category

• Intelligent Robots: Manipulation
• Planning, Routing, and Scheduling: Mixed Discrete/Continuous Planning
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking

Abstract

This paper presents a framework for aerial manipulation of an extensible cable that combines a high-fidelity model based on partial differential equations (PDEs) with a reduced-order representation suitable for real-time control. The PDEs are discretised using a finite-difference method, and proper orthogonal decomposition is employed to extract a reduced-order model (ROM) that retains the dominant deformation modes while significantly reducing computational complexity. Based on this ROM, a nonlinear model predictive control scheme is formulated, capable of stabilizing cable oscillations and handling hybrid transitions such as payload attachment and detachment. Simulation results confirm the stability, efficiency, and robustness of the ROM, as well as the effectiveness of the controller in regulating cable dynamics under a range of operating conditions. Additional simulations illustrate the application of the ROM for trajectory planning in constrained environments, demonstrating the versatility of the proposed approach. Overall, the framework enables real-time, dynamics-aware control of unmanned aerial vehicles (UAVs) carrying suspended flexible cables.

Problem

• nonlinear predictive control
• continuum dynamics
• hybrid dynamics
• suspended deformable cable
• aerial manipulation

Innovation

• Reduced-order modeling
• Nonlinear model predictive control
• Proper orthogonal decomposition
• Continuum dynamics
• Aerial manipulation