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Horizontal trajectory control of stratospheric airships in wind field using Q-learning algorithm
Aerospace Science and Technology ( IF 5.6 ) Pub Date : 2020-07-21 , DOI: 10.1016/j.ast.2020.106100
Xiaowei Yang , Xixiang Yang , Xiaolong Deng

This paper proposes an adaptive horizontal trajectory control method for stratospheric airships in uncertain wind field using Q-learning algorithm. Firstly, horizontal trajectory control of the airships is decomposed into the target tracking, and the observation model of airships is constructed. Then, the Markov decision process (MDP) model of airships is established, in which the action strategy is determined by the wind direction, and a cerebellar model articulation controller (CMAC) neural network is designed to optimize the action strategy for each state. Finally, numerical simulations demonstrate that the proposed control method performs well stability and intelligent decision-making ability in the process of horizontal trajectory control for stratospheric airships.



中文翻译:

基于Q学习算法的平流层飞艇在风场中的水平轨迹控制

提出了一种基于Q学习算法的平流层飞艇在不确定风场下的自适应水平轨迹控制方法。首先,将飞艇的水平轨迹控制分解为目标跟踪,建立了飞艇的观测模型。然后,建立了飞艇的马尔可夫决策过程(MDP)模型,其中的动作策略由风向确定,并且设计了小脑模型关节控制器(CMAC)神经网络来优化每种状态的动作策略。最后,数值仿真结果表明,所提出的控制方法在平流层飞艇的水平轨迹控制过程中具有良好的稳定性和智能决策能力。

更新日期:2020-07-21
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