Adaptive Fuzzy Fault-Tolerant Attitude Control for a Hypersonic Gliding Vehicle: A Policy-Iteration Approach

IF 2.2 3区 工程技术 Q2 ENGINEERING, MECHANICAL Actuators Pub Date : 2024-07-09 DOI:10.3390/act13070259
Meijie Liu, Changhua Hu, Hong Pei, Hongzeng Li, Xiaoxiang Hu
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Abstract

In this paper, adaptive fuzzy fault-tolerant control (AFFTC) for the attitude control system of a hypersonic gliding vehicle (HGV) experiencing an actuator fault is proposed. Actuator faults of the HGV are considered with respect to its actual structure and actuator characteristics. The HGV’s attitude system is firstly represented by a T–S fuzzy model, and then a normal T–S fuzzy controller is designed. A reinforcement learning (RL)-based policy iterative solution algorithm is proposed for the solving of the T-S fuzzy controller. Then, based on the normal T–S controller, a fuzzy FTC controller is proposed in which the control matrices can improve themselves according to the special fault. An integral reinforcement learning (IRL)-based solving algorithm is proposed to reduce the dependence of the design methods on the HGV model. Simulations on three different kinds of actuator faults show that the designed IRL-based FTC can ensure a reliable flight by the HGV.
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高超音速滑翔飞行器的自适应模糊容错姿态控制:策略迭代法
本文提出了针对执行器故障的高超音速滑翔飞行器(HGV)姿态控制系统的自适应模糊容错控制(AFFTC)。根据高超音速滑翔飞行器的实际结构和执行器特性考虑了其执行器故障。首先用 T-S 模糊模型表示 HGV 的姿态系统,然后设计普通 T-S 模糊控制器。针对 T-S 模糊控制器的求解,提出了一种基于强化学习(RL)的策略迭代求解算法。然后,在普通 T-S 控制器的基础上,提出了一种模糊 FTC 控制器,其中的控制矩阵可根据特殊故障进行自我改进。提出了一种基于积分强化学习(IRL)的求解算法,以减少设计方法对重型车辆模型的依赖。对三种不同执行器故障的仿真表明,所设计的基于 IRL 的 FTC 能够确保重型卡车可靠飞行。
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来源期刊
Actuators
Actuators Mathematics-Control and Optimization
CiteScore
3.90
自引率
15.40%
发文量
315
审稿时长
11 weeks
期刊介绍: Actuators (ISSN 2076-0825; CODEN: ACTUC3) is an international open access journal on the science and technology of actuators and control systems published quarterly online by MDPI.
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