Application of ML to System Identification for Underwater Vehicle

In this paper, maximum-likelihood (ML) and its relaxation algorithm, which are used to identify the mathematicsmodel of an underwater vehicle(UV), arc discussed. With the trial data of zigzag tests, the hydrodynamic derivatives of theUV were estimated, and the relaxation algorithm is confirmed to have better astringency from the contrast between the twomethods.Then a simulation environment based on these parameters is established to verify the validity and effect of these meth-ods. The result shows the model is credible and the methods are very useful for the research of maneuverability and adaptivecontrol of underwater vehicles.

Application of ML to system identification for underwater vehicle

In this paper, maximum- likelihood (ML) and its relaxation algorithm, which are used to identify the mathematics model of an underwater vehicle(UV), are discussed. With the trial data of zigzag tests, the hydrodynamic derivatives of the UV wore estimated, and the relaxation algorithm is confirmed to have better astringency from the contrast between the two methods. Then a simulation environment based on these parameters is established to verify the validity and effect of these methods. The result shows the model is credible and the methods arc very useful for the research of maneuverability and adaptive control of underwater vehicles.