Abstract

In this paper, the problem of CubeSat mobility is tackled. Two types of controllers are introduced to control the CubeSat Attitude Control System (ACS). PID and modified PI-D are applied to improve the mobility of the CubeSat along the three axes. Genetic Algorithm optimization (GAO) was applied to improve the performance of the CubeSat by tuning the controllers gains in the presence of external disturbances and white noise. The simulation results show the success of the introduced control approaches in solving the mobility problem for a CubeSat in the presence of external disturbances and white noise.

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