Three-axis gravity stabilization of 3U CubeSat is achieved due to selection of the nanosatellite moments of inertia at the design stage, as well as special modes included in the algorithm to provide stabilization of CubeSat relative to each motion channel separately. In this paper, we propose a modified algorithm based on the magnetic stabilization algorithm B-dot. The modified algorithm provides three modes intended to damp the initial angular velocity to the value of the orbital angular velocity, to keep the angular velocity at a value close to that of the orbital angular velocity, and to provide the nanosatellite gravitational triaxial stabilization by using one magnetic coil located on the axis with the transversal moment of inertia, which is possible due to the small angle between the magnetic field line and the satellite's trajectory. We propose two modifications for forming a control loop for orientation and stabilization of the 3U CubeSat: the first one uses measurements from magnetometers and angular rate sensors as feedback, and the second one, only magnetometers. The efficiency of the two modifications of modifications was studied by means of statistical modeling.
In this paper, we discuss the experience of development of a damping control system, based on the B-dot algorithm, for the SamSat unified nanosatellite platform. This platform was created by the center of testing and development of nanosatellites of Samara University. We divide the stabilization process into four repetitive phases: measuring, computing, control and delay for relaxation. Each phase has its particular duration, which significantly influences on the stabilization process. To use the B-dot algorithm, it is necessary to calculate the derivatives of the measured components of the Earth magnetic field induction in the body frame of nanosatellite. The SamSat nanosatellite platform has two three-axis magnetometers, which are characterized by a high noise level. To reduce the impact of this noise, the accumulated measurements are smoothed by the least square method. We provide recommendations for the selection of the damping algorithm parameters such as phase duration and polynomial degree. We conducted laboratory tests on magnetic test bench, following results proofs the efficiency of designed damping control system.
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