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现今,无人机的飞行控制系统主要基于PID控制系统。为了采用自适应智能控制系统来取代传统PID控制系统,建立四旋翼无人机仿真平台,实现无人机的自动续航航拍功能和对环境的自适应能力,给用户带来莫大的方便。该论文主要根据目前的人工智能水平和无人机的市场需求的设想和研究,放眼未来人们对于无人机市场的需求状况,提出结合传统PID控制和人工神经网络的控制方法,满足飞行器的任务需要和为未来人工智能在无人机的应用的进一步发展。
Today, UAV flight control systems are based primarily on PID control systems. In order to adopt the adaptive intelligent control system to replace the traditional PID control system, the establishment of four-rotor UAV simulation platform to achieve the UAV’s automatic endurance aerial photography and the ability to adapt to the environment, to the user a great convenience. Based on the current level of artificial intelligence and the market demand for UAVs, this dissertation focuses on the needs of the UAV market in the future and proposes a control method based on traditional PID control and artificial neural network to meet the requirements of the aircraft Need for and further development of UAV applications for the future of artificial intelligence.