SEP-NMPC: Safety Enhanced Passivity-Based Nonlinear Model Predictive Control for a UAV Slung Payload System
Seyedreza Rezaei, Junjie Kang, Amaldev Haridevan, Jinjun Shan
AI summary
Problem
Existing MPC controllers for UAV slung-payload systems typically lack formal closed-loop stability guarantees and fail to account for the swinging payload's expanded footprint, complicating safe navigation in cluttered environments.
Approach
The method embeds a strict passivity inequality to dissipate excess energy and ensure asymptotic stability, while using high-order control barrier functions to mathematically guarantee collision-free clearance for both the vehicle and swinging payload within a real-time quadratic program.
Key results
- Passivity-based energy shaping guarantees asymptotic stability of the underactuated system
- High-order control barrier functions ensure forward-invariant collision-free clearance for both vehicle and payload
- QP-compatible formulation enables seamless stability-safety integration without heuristic switching
- Real-time validation at 100 Hz confirms stable transport and obstacle avoidance in simulation and hardware
Why it matters
This framework enables reliable and safe aerial logistics and delivery missions in complex environments by mathematically guaranteeing both stability and obstacle avoidance for dynamically coupled UAV-payload systems.
Abstract
Model Predictive Control (MPC) is widely adopted for agile multirotor vehicles, yet achieving both stability and obstacle-free flight is particularly challenging when a payload is suspended beneath the airframe. This paper introduces a Safety Enhanced Passivity-Based Nonlinear MPC (SEP-NMPC) that provides formal guarantees of stability and safety for a quadrotor transporting a slung payload through cluttered environments. Stability is enforced by embedding a strict passivity inequality, which is derived from a shaped energy storage function with adaptive damping, directly into the NMPC. This formulation dissipates excess energy and en- sures asymptotic convergence despite payload swings. Safety is guaranteed through high-order control barrier functions (HOCBFs) that render user-defined clearance sets forward- invariant, obliging both the quadrotor and the swinging payload to maintain separation while interacting with static and dy- namic obstacles. The optimization remains quadratic-program compatible and is solved online at each sampling time without gain scheduling or heuristic switching. Extensive simulations and real-world experiments confirm stable payload transport, collision-free trajectories, and real-time feasibility across all tested scenarios. The SEP-NMPC framework therefore uni- fies passivity-based closed-loop stability with HOCBF-based safety guarantees for UAV slung-payload transportation. Video: https://youtu.be/l04DesGVjwc.