Swing State Estimation And Control Of Series-Connected Slung Payloads In Rotorcraft Transportation

Abstract

The use of rotorcraft with slung-load capabilities is increasingly relevant in applications ranging from aerial delivery to search-and-rescue. While existing research has extensively addressed single-payload systems, the present work investigates the estimation and control of swing dynamics in a rotorcraft transporting two serially-connected suspended payloads. A dynamic model of the system is derived via the Lagrangian approach, under the simplifying assumptions of point-mass vehicle and massless, rigid cables. The system is shown to be underactuated and its linearized dynamics about the hovering condition are used to formulate an estimation algorithm based on the Fading Gaussian Deterministic Filter (FGDF). This method uses only onboard accelerometer data to estimate swing angles and rates while minimizing the impact of model uncertainties and disturbances. The estimation is then embedded in a proportional feedback controller that stabilizes payload oscillations and maintains stability during dynamic events, such as load drop-off. The framework is validated through high-fidelity simulations of a heavy-lift octarotor. Results demonstrate improved swing suppression, energy efficiency, and operational continuity, confirming the approach's applicability to demanding aerial transport tasks and future urban delivery scenarios.