Tao Xinlong, Yi Jianqiang, Pu Zhiqiang, Xiong Tianyi
IEEE Trans Cybern. 2021 May;51(5):2504-2517. doi: 10.1109/TCYB.2019.2927309. Epub 2021 Apr 15.
This paper presents a novel robust adaptive tracking control method for a hypersonic vehicle in a cruise flight stage based on interval type-2 fuzzy-logic system (IT2-FLS) and small-gain approach. After the input-output linearization, the vehicle model can be decomposed into two uncertain subsystems by considering matching disturbances and parametric uncertainties. For each subsystem, an interval type-2 Takagi-Sugeno-Kang fuzzy logic system (IT2-TSK-FLS) is then employed to approximate the unavailable model information. Following the idea of a small-gain approach, a composite feedback form for each subsystem is constructed, based on which the final robust adaptive tracking control law is developed. Rigorous stability analysis shows that all signals in the derived closed-loop system are kept uniformly ultimately bounded (UUB). The main contribution of this paper is that the proposed control law for the hypersonic vehicle is with only two adaptive parameters in total which can greatly alleviate the computation and storage burden in practice; meanwhile its superiority over the conventional minimal-learning-parameter (MLP)-based one is specifically illustrated. Comparative numerical simulations of three cases demonstrate the effectiveness of our proposed control method with respect to complicated uncertainties.
本文提出了一种基于区间二型模糊逻辑系统（IT2-FLS）和小增益方法的高超声速飞行器巡航飞行阶段新型鲁棒自适应跟踪控制方法。在进行输入-输出线性化之后，通过考虑匹配干扰和参数不确定性，飞行器模型可分解为两个不确定子系统。对于每个子系统，采用区间二型Takagi-Sugeno-Kang模糊逻辑系统（IT2-TSK-FLS）来逼近未知的模型信息。遵循小增益方法的思想，为每个子系统构建一种复合反馈形式，并在此基础上设计最终的鲁棒自适应跟踪控制律。严格的稳定性分析表明，所推导闭环系统中的所有信号均保持一致最终有界（UUB）。本文的主要贡献在于，所提出的高超声速飞行器控制律总共仅具有两个自适应参数，这在实际中可极大地减轻计算和存储负担；同时具体说明了其相对于传统基于最小学习参数（MLP）方法的优越性。三种情况的对比数值仿真证明了我们所提控制方法对于复杂不确定性的有效性。
