Optimal Tuning of the Nanosatellite Attitude Controller Using TRIAD-Aided Kalman Filter and Particle Swarm Optimization

Satellite attitude control for nanosatellites is important research topic since the number of launched nanosatellites increasing year by year. Magnetic actuators are one of the most popular attitude control systems for them. A magnetic torquer is basic wrapped wire which current passes through itself. Interaction between generated magnetic dipole and magnetic field of Earth creates torque. It is also possible to use this magnetic torque to obtain three axis attitude control. PD controllers are basic control methods, that also can be applied to attitude control problem of a nanosatellite by magnetorquers. Accuracy of the controller can be affected from the gains. In this study, particle swarm optimization method is used to present a basic way to tune gains of PD controller for an accuracy increment. On the other hand, attitude knowledge of a satellite can be obtained from different attitude sensors. Since there is noise on these sensors, it is not possible to obtain exact knowledge of attitude. TRIAD (three axis attitude determination) method is used in this work with Earth-Sun sensors and magnetometer. Also, to decrease the effect of noise on the determination results, a basic Kalman filter is used. Simulation results show that, the proposed optimization strategy to optimize PD gains for nanosatellite attitude control with noisy measurements works well.