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The normal unscented Kalman filter (UKF) suffers from performance degradation and even divergence while mismatch between the noise distribution assumed to be known as a priori by UKF and the true ones in a real system. In this paper, a novel adaptive UKF (AUKF) is developed and applied to nonlinear joint estimation of both time-varying states and parameters. A cost function is built based on the error...
This paper proposes an unscented Kalman filter (UKF) based tracking controller to force underactuated nonlinear autonomous ships to follow a reference path under constant disturbances induced by wave, wind and ocean-current. The controller development is based on UKF and backstepping techniques. The UKF is used to update the estimation of the uncertain parameters online to avoid the parameters' drift...
Real time adaptability is of central importance for the control of unmanned helicopter flying under different circumstances. In this paper, an active model is employed to handle the time varying uncertainties involved in the helicopter dynamics during flight. In the scheme, a normal LQR control designed from a simplified model at hovering is enhanced by means of unscented-Kalman-filter (UKF) based...
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