Neural control of hypersonic flight dynamics with actuator fault and constraint

• Published in: Science China. Information sciences Vol. 58; no. 7; pp. 68 - 77
• Main Authors: Wang, ShiXing, Zhang, Yu, Jin, YuQiang, Zhang, YongQuan
• Format: Journal Article
• Language: English
• Published: Beijing Science China Press 01.07.2015; Springer Nature B.V
• Subjects: Actuators; Adaptive learning; Computer Science; High gain; Hypersonic flight; Information Systems and Communication Service; Lyapunov方法; Neural networks; Research Paper; Tracking errors; 执行器故障; 神经控制; 适应性学习; 飞行动力学; 饱和度; 高增益观测器; 高超声速飞行器; 070206; no back-stepping; longitudinal dynamics; neural network; stability; hypersonic flight vehicle
• ISSN: 1674-733X; 1869-1919
• DOI: 10.1007/s11432-015-5338-2

This paper deals with the control problem of actuator fault and saturation for hypersonic flight vehicles. Different from previous back-stepping design, the scheme is on transforming the dynamics into the ＂prediction function＂. The controller is constructed with high gain observer, while the effect of fault and saturation is compensated by neural networks. For the input saturation, the auxiliary dynamics is included to design the adaptive learning law. The neural weights and filtered tracking error are guaranteed to be bounded via Lyapunov approach. The effectiveness of the proposed method is verified by simulation of winged-cone model.