Abstract
This paper presents the design, implementation, and flight test results of two novel 3D path-following guidance algorithms based on nonlinear model predictive control (MPC), with specific application to fixed-wing small uncrewed aircraft systems. To enable MPC, control-augmented modelling and system identification of the RAAVEN small uncrewed aircraft is presented. Two formulations of MPC are then showcased. The first schedules a static reference path rate over the MPC horizon, incentivizing a constant inertial speed. The second, with inspiration from model predictive contouring control, dynamically optimizes for the reference path rate over the controller horizon as the system operates. This allows for a weighted tradeoff between path progression and distance from path, two competing objectives in path-following guidance. Both controllers are formulated to operate over general smooth 3D arc-length parameterized curves. The MPC guidance algorithms are flown over several high-curvature test paths, with comparison to a baseline lookahead guidance law. The results showcase the real-world feasibility and superior performance of nonlinear MPC for 3D path-following guidance at ground speeds up to 36 meters per second.
Abstract (translated)
本文介绍了两种基于非线性模型预测控制（MPC）的新型三维路径跟踪引导算法的设计、实现及飞行测试结果，这些算法专门应用于固定翼小型无人驾驶飞机系统。为了启用MPC，文中展示了对RAAVEN小型无人驾驶飞机的增控建模和系统识别过程。然后，介绍了两种MPC的构型。 第一种方法在整个模型预测控制时域内安排静态参考路径速率，旨在激励恒定惯性速度。第二种方法受到模型预测轮廓控制的启发，在控制器操作期间动态优化参考路径速率。这使得在路径跟踪引导中两个竞争目标——路径进展和远离路径的距离之间可以进行加权折衷。 这两种控制器都设计为可以在通用平滑三维弧长参数化曲线范围内运行。MPC引导算法已在多个高曲率测试路径上进行了飞行，与基线前瞻式导引法则进行了比较。结果表明，在高达每秒36米的速度下，非线性MPC在三维路径跟踪中的实际可行性及其优越性能。
URL
https://arxiv.org/abs/2512.24326
