Neural network based adaptive nonsingular practical predefined-time fault-tolerant control for hypersonic morphing aircraft

作     者：Shihao XU Changzhu WEI Litao ZHANG Rongjun MU Shihao XU;Changzhu WEI;Litao ZHANG;Rongjun MU

作者机构：School of AstronauticsHarbin Institute of TechnologyHarbin 150001China Beijing Institute of Control&Electronics TechnologyBeijing 100038China 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2024年第37卷第4期

页      面：421-435页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 081105[工学-导航、制导与控制] 0835[工学-软件工程] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China (Nos. 52233014  U2241215) 

主　　题：Hypersonic morphing aircraft(HMA) Neural network(NN) Adaptive control Practical predefined-time control Fault-tolerant control 

摘      要：This paper develops a novel Neural Network(NN)-based adaptive nonsingular practical predefined-time controller for the hypersonic morphing aircraft subject to actuator faults. Firstly, a novel Lyapunov criterion of practical predefined-time stability is established. Following the proposed criterion, a tangent function based nonsingular predefined-time sliding manifold and the control strategy are developed. Secondly, the radial basis function NN with a low-complexity adaptation mechanism is incorporated into the controller to tackle the actuator faults and uncertainties. Thirdly, rigorous theoretical proof reveals that the attitude tracking errors can converge to a small region around the origin within a predefined time, while all signals in the closed-loop system remain bounded. Finally, numerical simulation results are presented to verify the effectiveness and improved performance of the proposed control scheme.