Swarm intelligence
System Dynamics: Modeling and Simulation of Mechatronic Systems
System Dynamics: Modeling and Simulation of Mechatronic Systems
Analysis of the publications on the applications of particle swarm optimisation
Journal of Artificial Evolution and Applications - Regular issue
Neural network based three axis satellite attitude control using only magnetic torquers
NN'05 Proceedings of the 6th WSEAS international conference on Neural networks
Fully magnetic attitude control for spacecraft subject to gravity gradient
Automatica (Journal of IFAC)
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Satellite state control has always been an important topic in aerospace technology. Because it is required that when the satellite is stationary in orbit, it would be directed to a special object and this task should be performed in a situation where there isn't access to the satellite. This task is performed using various technologies and one of these is the use of magnetic actuators. Magnetic actuators use mechanical torque that is resulted by interaction of electrical current of coils in the satellite and the earth's magnetic field. The satellite is subjected to such disturbance torques, thus corrupting the direction of the satellite. This method has its advantages and disadvantages. Its drawback is that the magnetic torque is produced only perpendicular to the direction of the magnetic field and the axis of the coil. This paper models a satellite having magnetic actuators using bond graph, and finds out its state equations, and then constructs the control logic that is needed for its control. A model of three dimensional attitude maneuvers and magnetic systems using bond graph is described. The actuators are tuned using the method of particle swarm optimization PSO. It is observed that using this method a small satellite reaches to the desired angle in a short time and becomes stationary.