Prescribed-Time Cooperative Integrated Guidance and Control for Reentry Vehicle Based on Hybrid Control Strategy

IF 3.2 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

International Journal of Robust and Nonlinear Control Pub Date : 2025-04-25 DOI:10.1002/rnc.8012

Lei Cui, Zhe Zhen, Zhicheng Zhang

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引用次数: 0

Abstract

In this paper, a prescribed-time cooperative integrated guidance and control (PTCIGC) is designed for reentry vehicles to achieve cooperative guidance and control. This method is designed based on bank-to-turn and skid-to-turn (BTT-STT) hybrid control strategy. Firstly, an IGC model of the reentry vehicle is established, which can be divided into three subsystems: Relative motion subsystem, airflow angle subsystem, and three-channel angle rate subsystem. Secondly, a prescribed-time controller is designed for the relative motion subsystem to obtain the airflow angle commands. Thirdly, a prescribed-time sliding mode controller (SMC) is designed for the airflow angle subsystem to track the airflow angle commands. Fourthly, to track the three-channel angle rate commands, a prescribed-time disturbance observer (DO) based on prescribed-time SMC is designed. Finally, the effectiveness of the PTCIGC method proposed in this paper is verified by six-degree-of-freedom (6DoF) numerical simulation in three-dimensional (3D) space.

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基于混合控制策略的再入飞行器定时协同综合制导与控制

为实现再入飞行器的协同制导与控制，设计了一种定时协同综合制导与控制（PTCIGC）。该方法基于倾斜转向和滑动转向（BTT-STT）混合控制策略设计。首先，建立了再入飞行器的IGC模型，将其划分为相对运动子系统、气流角子系统和三通道角率子系统。其次，为相对运动子系统设计了规定时间控制器，以获取气流角指令。第三，为气流角子系统设计了定时滑模控制器（SMC）来跟踪气流角指令。第四，为了跟踪三通道角速率指令，设计了基于定时SMC的定时扰动观测器（DO）。最后，通过三维空间的六自由度（6DoF）数值模拟验证了本文提出的PTCIGC方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Robust and Nonlinear Control 工程技术-工程：电子与电气

CiteScore

6.70

自引率

20.50%

发文量

505

审稿时长

2.7 months

期刊介绍： Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.