Novel adaptive neural control of flexible air-breathing hypersonic vehicles based on sliding mode differentiator

作     者：Bu Xiangwei Wu Xiaoyan Ma Zhen Zhang Rui 

作者机构：Air and Missile Defense College Air Force Engineering University 

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

年 卷 期：2015年第28卷第4期

页      面：1209-1216页

核心收录：

学科分类：08[工学] 081105[工学-导航、制导与控制] 0802[工学-机械工程] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 0801[工学-力学（可授工学、理学学位）] 

基　　金：supported by the Aeronautical Science Foundation of China (No.20130196004) 

主　　题：Adaptive neural control Flexible air-breathing hyper-sonic vehicle (FAHV) Flexible effects Minimal-learning parameter(MLP) Sliding mode differentiator(SMD) 

摘      要：A novel adaptive neural control strategy is exploited for the longitudinal dynamics of a generic flexible air-breathing hypersonic vehicle（FAHV）.By utilizing functional decomposition method, the dynamics of FAHV is decomposed into the velocity subsystem and the altitude *** each subsystem, only one neural network is employed for the unknown function *** further reduce the computational burden, minimal-learning parameter（MLP）technology is used to estimate the norm of ideal weight vectors rather than their *** introducing sliding mode differentiator（SMD） to estimate the newly defined variables, there is no need for the strict-feedback form and virtual *** the developed control law is considerably simpler than the ones derived from back-stepping ***, simulation studies are made to illustrate the effectiveness of the proposed control approach in spite of the flexible effects, system uncertainties and varying disturbances.