.png){kind=icon}
返回
Reinforcement learning based closed-loop reference model adaptive flight control system design
.png){kind=icon}
OA
AI
DOI：10.1002/acs.3181.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this study, we present a reinforcement learning (RL)-based flight control system design method to improve the transient response performance of a closed-loop reference model (CRM) adaptive control system. The methodology, known as RL-CRM, relies on the generation of a dynamic adaption strategy by implementing RL on the variable factor in the feedback path gain matrix of the reference model. An actor-critic RL agent is designed using the performance-driven reward functions and tracking error observations from the environment. In the training phase, a deep deterministic policy gradient algorithm is utilized to learn the time-varying adaptation strategy of the design parameter in the reference model feedback gain matrix. The proposed control structure provides the possibility to learn numerous adaptation strategies across a wide range of flight and vehicle conditions instead of being driven by high-fidelity simulators or flight testing and real flight operations. The performance of the proposed system was evaluated on an identified and verified mathematical model of an agile quadrotor platform. Monte-Carlo simulations and worst case analysis were also performed over a benchmark helicopter example model. In comparison to the classical model reference adaptive control and CRM-adaptive control system designs, the proposed RL-CRM adaptive flight control system design improves the transient response performance on all associated metrics and provides the capability to operate over a wide range of parametric uncertainties.
Keyword:
adaptive flight control system
reinforcement learning
resilient control
variable closed-loop reference model adaptive control
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.8
论文数:
2.6K
被引数:
3.6K
机构
引用论文
.png){kind=icon}
分享收藏Adaptive Control of Quadrotor UAVs: A Design Trade Study With Flight Evaluations四旋翼无人机的自适应控制: 带有飞行评估的设计贸易研究
PREAI
分享收藏分享收藏
查看更多内容