Nonliner control for autonomous underwater vehicles using group method of data handling

In this paper, we deal with an attitude control for autonomous underwater vehicles (AUVs) incorporating estimation of unknown parameters. AUVs are used for deep ocean research, searching fish bed, etc. It is very difficult to control their attitude, because the model of AUVs are described as high order nonlinear system containing some parameters difficult to measure. According to the existing research, there are suggestions for estimating unknown parameters using nonlinear estimator with online control. However, these nonlinear estimators tend to be unstable due to initial estimated error and observation noise. Therefore, we design an input-output linearization controller with Group Method of Data Handling (GMDH) for the parameter identification. First, we check the availability of our method on 2-D model of AUVs. Secondly, we extend the existing input-output linearization technique for the model to 6-degree of freedom which has a lot of unknown parameters. Then, we demonstrate the effectiveness of our control design through numerical simulations.