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.

翻译：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制导算法的设计、实现与飞行测试结果，并特别应用于固定翼小型无人航空系统。为实现MPC，本文提出了RAAVEN小型无人机的控制增强建模与系统辨识方法。随后展示了两种MPC的构建方案。第一种方案在MPC预测时域内调度静态的参考路径速率，从而激励恒定的惯性速度。第二种方案受模型预测轮廓控制启发，在系统运行过程中动态优化控制器时域内的参考路径速率。这使得路径推进与路径偏移距离这两个在路径跟踪制导中相互竞争的目标能够进行加权权衡。两种控制器均被构建为可在通用的光滑三维弧长参数化曲线上运行。MPC制导算法在多个高曲率测试路径上进行了飞行验证，并与基准前瞻制导律进行了比较。结果表明，非线性MPC在高达每秒36米的地速条件下，用于三维路径跟踪制导具有实际可行性及优越性能。