Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
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The objective of this paper is to develop an intelligent fuzzy attitude control strategy for detumbling with initial spin-up phase and spin rate control for small, low earth orbit satellite using only magnetometer and torquer. A magnetic moment produced by coils placed on the satellite will produce a resultant torque by interaction with the geomagnetic field, which may be used for attitude control purposes. Nevertheless, this simple, low power consumption approach poses several interesting control difficulties as the geomagnetic field viewed by a satellite, changes along its orbit. Besides this time dependency, this problem's mathematical description is highly non-linear, and hence a new intuitive control strategy is needed to solve the attitude and control demands of such a satellite. In this work, controllers are designed which, consists of Multi Input Multi Output (MIMO) fuzzy logic controllers. Also Single Input Single Output controllers are used to control the spin rate. This fuzzy control approach ensures the required performance in the presence of disturbance, uncertainty and various non-linearities and also describes the design of rule based fuzzy logic controller. This structure of the controller takes advantage of classical controllers while maintaining a significant degree of robustness, performance and portability. Furthermore, Simulation studies are illustrated for such control scheme.