Abstract
Complex space missions involving large angle maneuvers and fast attitude control require nonlinear control methods to design the Satellite Controller System (SCS) in order to satisfy robustness and performance requirements. One candidate method for a nonlinear SCS control law is the State-Dependent Riccati Equation (SDRE). SDRE provides an effective algorithm for synthesizing nonlinear feedback control by allowing nonlinearities in the system states while offering great design flexibility through state-dependent weighting matrices. In that context, analysis by simulation of nonlinear control methods can save money and time. Although, commercial 3D simulators exist that can accommodate various satellites components including the controllers, in this paper, we present a 3D simulator and the investigation of a SDRE control law performance by simulations. The simulator is implemented based on Java and related open-source software libraries (Hipparchus - linear algebra library, and Orekit - flight dynamics library), therefore, it can run in a variety of platforms and it has low cost. These open-source libraries were extended in order to solve the optimization problem that is the cornerstone of the SDRE method, a major contribution of the simulator. The simulator is evaluated taking into account a typical mission of the Brazilian National Institute for Space Research (INPE), in which the SCS must stabilize a satellite in three-axis using reaction wheels so that the optical payload can point to the desired target. Two SCS control laws (a linear and a SDRE based) were simulated for an attitude maneuver in the launch and early orbit phase (LEOP), the upside-down maneuver. The results of simulations shown that SDRE-based controller provides better performance.
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Romero, A.G., de Souza, L.C.G. (2019). Satellite Controller System Based on Reaction Wheels Using the State-Dependent Riccati Equation (SDRE) on Java. In: Cavalca, K., Weber, H. (eds) Proceedings of the 10th International Conference on Rotor Dynamics – IFToMM . IFToMM 2018. Mechanisms and Machine Science, vol 61. Springer, Cham. https://doi.org/10.1007/978-3-319-99268-6_38
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