Six-DOF spacecraft optimal trajectory planning and real-time attitude control: a deep neural network-based approach

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dc.contributor.authorChai, Runqi
dc.contributor.authorTsourdos, Antonios
dc.contributor.authorSavvaris, Al
dc.contributor.authorChai, Senchun
dc.contributor.authorXia, Yuanqing
dc.contributor.authorChen, C. L. Philip
dc.date.accessioned2020-03-11T11:15:10Z
dc.date.available2020-03-11T11:15:10Z
dc.date.issued2019-12-12
dc.description.abstractThis 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.en_UK
dc.identifier.citationChai R, Tsourdos A, Savvaris A, et al., (2019) 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, Volume 31, Issue 11, November 2020, pp. 5005-5013en_UK
dc.identifier.issn2162-237X
dc.identifier.urihttps://doi.org/10.1109/TNNLS.2019.2955400
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/15270
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectAttitude controlen_UK
dc.subjectbilevel structureen_UK
dc.subjectdeep neural network (DNN)en_UK
dc.subjectsix-degree-of-freedom (6-DOF)en_UK
dc.subjecthypersonic vehicle (HV)en_UK
dc.subjecttrajectory planningen_UK
dc.titleSix-DOF spacecraft optimal trajectory planning and real-time attitude control: a deep neural network-based approachen_UK
dc.typeArticleen_UK

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