Control of a class of uncertain nonlinear systems, which estimates unavailable state variables, is considered. A new approach for robust tracking control problem of satellite for large rotational maneuvers is presented in this paper. The features of this approach include a strong algorithm to estimate attitude, based on discrete extended Kalman filter combined with a continuous extended Kalman filter and attitude nonlinear model, and a robust controller based on sliding-mode with perturbation estimation. Estimation accuracy in this method is five times higher than other recent approaches based on Kalman filter. We have used sliding-mode controller in this paper. Not only the controller and the corresponding observer but also their composition must be robust. To make this controller robust against the uncertainty of parameters, the robust Kalman filter is used. Based on interval algebra, an upper bound and a lower bound are estimated for state variables of the system and considering these bounds in indicating the sliding conditions, stability of the controller in combination with the observer will be satisfied simultaneously. The simulation results show the capability of this method in spite of different uncertainty levels (up to %50).
M. Jafarboland, , N. Sadati, , & and H. R. Momeni, (2022). Robust Tracking Control of Satellite Attitude Using New EKF for Large Rotational Maneuvers. Journal of Computational Methods in Engineering, 25(1), 1-15.
MLA
M. Jafarboland; N. Sadati; and H. R. Momeni. "Robust Tracking Control of Satellite Attitude Using New EKF for Large Rotational Maneuvers", Journal of Computational Methods in Engineering, 25, 1, 2022, 1-15.
HARVARD
M. Jafarboland, , N. Sadati, , and H. R. Momeni, (2022). 'Robust Tracking Control of Satellite Attitude Using New EKF for Large Rotational Maneuvers', Journal of Computational Methods in Engineering, 25(1), pp. 1-15.
VANCOUVER
M. Jafarboland, , N. Sadati, , and H. R. Momeni, Robust Tracking Control of Satellite Attitude Using New EKF for Large Rotational Maneuvers. Journal of Computational Methods in Engineering, 2022; 25(1): 1-15.