@InProceedings{SilvaRios:2000:NePrSa,
author = "Silva, Jaime Augusto da Silva and Rios Neto, Atair",
title = "Neural predictive satellite attitude control based on Kalman
filtering algorithms",
booktitle = "Proceedings...",
year = "2000",
organization = "International Symposium Space Dynamics.",
keywords = "ENGENHARIA E TECNOLOGIA ESPACIAL, attitude control, Kalman
filtering.",
abstract = "An artificial neural network predictive control scheme considered
for satellite attitude control. Kalman filtering algorithms are
used only to train the associated feedforward neural network
modeling the dynamics the plant but to also estimate the control
actions. It is shown that the optimization of a predictive
quadratic performance functional, used to determine the discrete
control actions, can be viewed and treated, in a typical
iteration, as a stochasti optimal linear parameter estimation
problem. The algorithms obtained are shown to be the result of
application of Newton's method to appropriate control optimization
functionals that provide solutions that converge to smooth and
reference tracking controls. The proposed scheme is then applied
to a three-axes satellite attitude control with a double-gimbaled
momentum wheel. Results on simulations and tests for the situation
of fine pointing torques and errors in the initial satellite
attitude show excellent performance of the proposed scheme.",
conference-location = "Bearritz, FR",
conference-year = "26-30 June 2000",
label = "10182",
organisation = "CNES",
targetfile = "9261.pdf",
urlaccessdate = "07 maio 2024"
}