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