NDLI: Neural network based three axis satellite attitude control using only magnetic torquers

Content Provider	IEEE Xplore Digital Library
Author	Sivaprakash, N. Shanmugam, J.
Copyright Year	2005
Description	Author affiliation: Dept. of Electron. Eng., MIT-Anna Univ., Chennai, India (Sivaprakash, N.; Shanmugam, J.)
Abstract	Magnetic actuation utilizes the mechanic torque that is the result of interaction of the current in a coil with an external magnetic field. A main obstacle is, however, that torques can only be produced perpendicular to the magnetic field. In addition, there is uncertainty in the Earth magnetic field models due to the complicated dynamic nature of the field. Also, the magnetic hardware and the spacecraft can interact, causing both to behave in undesirable ways. This actuation principle has been a topic of research since earliest satellites were launched. Earlier magnetic control has been applied for nutation damping for gravity gradient stabilized satellites, and for velocity decrease for satellites without appendages. The three axes of a micro-satellite can be stabilized by using an electromagnetic actuator which is rigidly mounted on the structure of the satellite. The actuator consists of three mutually-orthogonal air-cored coils on the skin of the satellite. The coils are excited so that the orbital frame magnetic field and body frame magnetic field coincides i.e. to make the Euler angles to zero. This can be done using a neural network controller trained by PD controller data and driven by the difference between the orbital and body frame magnetic fields.
File Size	381158
File Format	PDF
ISBN	0780393074
DOI	10.1109/DASC.2005.1563440
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Satellites Magnetic fields Coils Actuators Torque Uncertainty Earth Hardware Space vehicles
Content Type	Text
Resource Type	Article

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