15 / 2021-02-25 20:39:59
Investigating Satellite Attitude and Orbit Control System Performance of the SDRE Technique regarding Parametric Uncertainty
Riccati,SDRE,Control,H-Infinity,Nonlinear
全文录用
Alessandro Romero / National Institute for Space Research
Luiz Carlos Gadelha de Souza / Universidade Federal do ABC
The satellite attitude and orbit control subsystem (AOCS) can be designed with success by linear control theory if the satellite has slow angular motions. However, for fast manoeuvres, the linearized models are not able to represent all the perturbations due to the effects of the nonlinear terms present in the dynamics. Therefore, in such cases, it is expected that nonlinear control techniques yield better performance than the linear control techniques. Nonetheless, these nonlinear techniques can be more sensitive to parametric uncertainties. One candidate technique for the design of AOCS control law under a fast maneuver is the State-Dependent Riccati Equation (SDRE). SDRE provides an effective algorithm for synthesizing nonlinear feedback control by allowing nonlinearities in the system states. The Brazilian National Institute for Space Research (INPE) was demanded by the Brazilian government to build remote-sensing satellites, such as the Amazonia-1 mission. In such missions, the AOCS must stabilize the satellite in three-axes so that the optical payload can point to the desired target. Although elsewhere the application of the SDRE technique with opensource software has shown to yield better performance for the missions developed by INPE, a subsequent important question is whether such better performance is robust to parametric uncertainties. In this paper, we investigate whether the application of the SDRE technique in the AOCS is robust to parametric uncertainties in the missions developed by INPE. The initial results showed that SDRE controller is robust to ±5%, at least, variations in the inertia tensor of the satellite.
重要日期
  • 会议日期

    11月01日

    2022

    11月03日

    2022

  • 10月30日 2022

    初稿截稿日期

  • 11月09日 2022

    注册截止日期

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