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Switching control of morphing aircraft based on Q-learning

Switching control of morphing aircraft based on Q-learning

作     者:Ligang GONG Qing WANG Changhua HU Chen LIU Ligang GONG;Qing WANG;Changhua HU;Chen LIU

作者机构:School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083China Science and Technology on Space Intelligent Control LaboratoryBeijing Institute of Control EngineeringBeijing 100190China Xi’an Institute of High TechnologyXi’an 710025China School of Aeronautic Science and EngineeringBeihang UniversityBeijing 100083China Beijing Institute of Electric System EngineeringBeijing 100854China 

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

年 卷 期:2020年第33卷第2期

页      面:672-687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 National Natural Science Foundation of China(Nos.61873295,61833016) the Aeronautical Science Foundation of China(No.2016ZA51011) 

主  题:Back-stepping Command filter Disturbance observer Morphing aircraft Q-learning Switching control 

摘      要:This paper investigates a switching control strategy for the altitude motion of a morphing aircraft with variable sweep wings based on *** morphing process is regarded as a function of the system states and a related altitude motion model is ***,the designed controller is divided into the outer part and inner part,where the outer part is devised by a combination of the back-stepping method and command filter technique so that the’explosion of complexity’problem is ***,the integrator structure of the altitude motion model is exploited to simplify the back-stepping design,and disturbance observers inspired from the idea of extended state observer are devised to obtain estimations of the system *** control input switches from the outer part to the inner part when the altitude tracking error converges to a small value and linear approximation of the altitude motion model is *** inner part is generated by the Q-learning algorithm which learns the optimal command in the presence of unknown system matrices and *** is proved rigorously that all signals of the closed-loop system stay bounded by the developed control method and controller switching occurs only ***,comparative simulations are conducted to validate improved control performance of the proposed scheme.

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