Fixed-Time Neural Control for Hypersonic Flight Vehicles with Asymmetric Time-Varying Constraints

• Published in: Journal of physics. Conference series Vol. 1966; no. 1; pp. 12050 - 12055
• Main Authors: Dong, Zehong, Li, Yinghui, Xu, Haojun, Li, Zhe, Pei, Binbin, Zheng, Wuji
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.07.2021
• Subjects: Adaptive control; Asymmetry; Dynamic stability; Flight vehicles; Hypersonic flight; Mathematical analysis; Neural networks; Operators (mathematics); Radial basis function; Tracking control; Tracking errors
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/1966/1/012050

This paper presents a novel fixed-time adaptive tracking control scheme for the hypersonic flight vehicles (HFVs) subject to asymmetric time-varying constraints, uncertain dynamics and unknown external disturbances. By incorporating the back-stepping technique and radial basis function neural networks (RBFNNs), the uncertain dynamics of HFVs are estimated. Note that most existing results only achieve practical fixed-time stability but not fixed-time stability, or require specific knowledge of all the dynamics of HFVs. To remove such restrictions, a fixed-time controller is newly constructed by means of a tuning functions and a projection operator-based adaptation mechanism. In consequence, the tracking errors can asymptotically converge to the preassigned compact set within fixed-time and the asymmetric time-varying constraints of HFVs never are violated. Finally, the effectiveness and superiority of the proposed control strategy is demonstrated by numerical simulations.