This paper describes an approach to neural control of a satellite trajectory. A pseudolinear model is created to generate the necessary training data for the neural network. This model uses an H∞ to stabilize the relative motion of a satellite concerning another satellite. The purpose of this paper is to show the feasibility of such an approach and to better understand the benefits of using a previously trained neural network to control a satellite.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Neural Control of Space Trajectories with Pseudolinear Models


    Additional title:

    Sustainable aviat.



    Conference:

    International Symposium on Aviation Technology, MRO, and Operations ; 2022 ; Belgrade, Serbia September 14, 2022 - September 16, 2022



    Publication date :

    2023-11-23


    Size :

    6 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





    Nonlinear Shannon Limit in Pseudolinear Coherent Systems

    Mecozzi, A. / Essiambre, R.-J. | British Library Online Contents | 2012



    Biased Estimation Properties of the Pseudolinear Tracking Filter

    Aidala, Vincent J. / Nardone, Steven C. | IEEE | 1982


    Nonlinear Shannon Limit in Pseudolinear Coherent Systems (Invited Paper)

    Mecozzi, A. / Essiambre, R.-J. | British Library Online Contents | 2012