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Six-DOF Spacecraft Optimal Trajectory Planning and Real-Time Attitude Control: A Deep Neural Network-Based Approach

文献类型：期刊论文

作者Chai, Runqi2; Tsourdos, Antonios2; Savvaris, Al2; Chai, Senchun3; Xia, Yuanqing3; Chen, C. L. Philip1,4,5
刊名IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
出版日期2020-11-01
卷号31期号:11页码:5005-5013
关键词Attitude control Real-time systems Trajectory optimization Trajectory planning Attitude control bilevel structure deep neural network (DNN) six-degree-of-freedom (6-DOF) hypersonic vehicle (HV) trajectory planning
ISSN号2162-237X
DOI10.1109/TNNLS.2019.2955400
通讯作者Chai, Runqi(r.chai@cranfield.ac.uk)
英文摘要This brief presents an integrated trajectory planning and attitude control framework for six-degree-of-freedom (6-DOF) hypersonic vehicle (HV) reentry flight. The proposed framework utilizes a bilevel structure incorporating desensitized trajectory optimization and deep neural network (DNN)-based control. In the upper level, a trajectory data set containing optimal system control and state trajectories is generated, while in the lower level control system, DNNs are constructed and trained using the pregenerated trajectory ensemble in order to represent the functional relationship between the optimized system states and controls. These well-trained networks are then used to produce optimal feedback actions online. A detailed simulation analysis was performed to validate the real-time applicability and the optimality of the designed bilevel framework. Moreover, a comparative analysis was also carried out between the proposed DNN-driven controller and other optimization-based techniques existing in related works. Our results verify the reliability of using the proposed bilevel design for the control of HV reentry flight in real time.
WOS关键词OPTIMIZATION ; VEHICLES ; TRACKING ; GUIDANCE ; DESIGN ; SYSTEM
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000587699700048
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://ir.ia.ac.cn/handle/173211/41726]  
专题离退休人员
通讯作者Chai, Runqi
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100080, Peoples R China
2.Cranfield Univ, Sch Aerosp Transport & Mfg, Bedford MK43 0AL, England
3.Beijing Inst Technol, Sch Automat, Beijing 100811, Peoples R China
4.Univ Macau, Fac Sci & Technol, Macau 999078, Peoples R China
5.Dalian Maritime Univ, Dept Nav, Dalian 116026, Peoples R China
推荐引用方式
GB/T 7714		 Chai, Runqi,Tsourdos, Antonios,Savvaris, Al,et al. Six-DOF Spacecraft Optimal Trajectory Planning and Real-Time Attitude Control: A Deep Neural Network-Based Approach[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2020,31(11):5005-5013.
APA Chai, Runqi,Tsourdos, Antonios,Savvaris, Al,Chai, Senchun,Xia, Yuanqing,&Chen, C. L. Philip.(2020).Six-DOF Spacecraft Optimal Trajectory Planning and Real-Time Attitude Control: A Deep Neural Network-Based Approach.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,31(11),5005-5013.
MLA Chai, Runqi,et al."Six-DOF Spacecraft Optimal Trajectory Planning and Real-Time Attitude Control: A Deep Neural Network-Based Approach".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 31.11(2020):5005-5013.

入库方式： OAI收割

来源：自动化研究所

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