Range-Varying Sliding Mode-Based Integrated Guidance and Control for Hypersonic Vehicle With Multi-Constraints

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Weiping Xu, Yuxin Liao, Xin Wang, Caisheng Wei, Zeyang Yin, Qifeng Chen
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Abstract

This paper proposes a novel integrated guidance and control (IGC) scheme for a bank-to-turn (BTT) hypersonic vehicle (HV) in the dive phase with multi-constraints, input saturation, and complex uncertainties. In the guidance loop, the presence of the terminal impact angle constraints may cause severe saturation of the attack angle, which may lead to the failure of the mission. Motivated by this issue, a range-varying sliding mode surface is constructed, of which the core is a novel line-of-sight (LOS) angle error shaping strategy that drives the LOS angle errors to converge along the prescribed performance functions. On this basis, a range-based prescribed performance function is designed to portray a practical saturation-alleviation convergence characteristic of the LOS angle errors. In the control loop, the barrier Lyapunov function (BLF) and barrier function (BF)-based adaptive law are incorporated to restrict the states within proper regions in the presence of uncertainties. Additionally, an auxiliary system is constructed to deal with the adverse affect caused by input saturation. The stability of the closed-loop system is proved by the Lyapunov stability theory. Finally, the effectiveness and robustness of the proposed IGC scheme are verified through numerical simulations.

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来源期刊
International Journal of Robust and Nonlinear Control
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.
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