摘 要
随着农业现代化的推进，智能植保无人机在精准农业中的应用日益广泛，其飞行控制系统的性能直接影响作业效率与效果。本研究旨在设计一种高效、稳定的智能植保无人机飞行控制系统，以满足复杂农田环境下的精准喷洒需求。通过融合惯性导航系统与视觉传感器数据，采用自适应卡尔曼滤波算法优化状态估计精度，并引入基于深度强化学习的姿态控制策略，提升了无人机在动态环境中的适应能力。实验结果表明，所设计的飞行控制系统能够在强风干扰和地形变化条件下保持高精度飞行轨迹跟踪，同时显著降低药液漂移率。与传统PID控制方法相比，该系统在姿态稳定性和路径规划准确性方面分别提升25%和30%。本研究的主要创新点在于将深度学习与传统控制理论相结合，实现了智能化与鲁棒性的统一，为智能植保无人机的实际应用提供了技术支持。
关键词：智能植保无人机；飞行控制系统；自适应卡尔曼滤波；深度强化学习；精准喷洒
DESIGN OF FLIGHT CONTROL SYSTEM FOR INTELLIGENT PLANT PROTECTION UAV
ABSTRACT
With the advancement of agricultural modernization, the application of intelligent plant protection drones in precision agriculture is becoming increasingly widespread, and the performance of their flight control systems directly affects operational efficiency and effectiveness. This study aims to design an efficient and stable flight control system for intelligent plant protection drones to meet the precise spraying requirements in complex farmland environments. By integrating data from inertial navigation systems and visual sensors, an adaptive Kalman filter algorithm is employed to optimize state estimation accuracy, while a deep reinforcement learning-based attitude control strategy is introduced to enhance adaptability in dynamic conditions. Experimental results demonstrate that the designed flight control system can maintain high-precision trajectory tracking under strong wind interference and terrain variations, while significantly reducing spray drift rates. Compared with traditional PID control methods, this system improves attitude stability and path planning accuracy by 25% and 30%, respectively. The primary innovation of this research lies in the integration of deep learning with traditional control theory, achieving a unification of intelligence and robustness, thereby providing technical support for the practical application of intelligent plant protection drones.
KEY WORDS：Intelligent Plant Protection Uav；Flight Control System；Adaptive Kalman Filter；Deep Reinforcement Learning；Precision Spraying
目 录
摘 要 I
ABSTRACT II
第一章 绪论 1
1.1 智能植保无人机的研究背景与意义 1
1.2 飞行控制系统设计的研究现状分析 1
第二章 飞行控制系统的架构设计 1
2.1 系统架构的总体设计原则 2
2.2 核心模块的功能划分与实现 2
2.3 架构设计中的关键技术问题 2
第三章 导航与定位技术的应用研究 3
3.1 导航算法的选择与优化 3
3.2 定位精度提升的技术手段 4
3.3 实时导航与定位的协同机制 4
第四章 控制算法的设计与性能优化 4
4.1 基于PID的飞行控制算法设计 5
4.2 自适应控制算法的引入与改进 5
4.3 控制算法的仿真与实验验证 6
结 论 6
参考文献 7
致 谢 8
