6-DOF AUV Identification with MIMO-NARX

This paper applies the MIMO NARX neural model to identify AUV with six degrees of freedom. Strongly nonlinear dependencies are modeled using a MIMO NARX model trained using «input-output» experimental data. This results in a grey box model with a partially known internal structure that can be supervised. This is achieved by specifying a certain regressors type, which is feedback to the model input. Obtained results show that the neural model trained by the Levenberg–Marquardt numerical algorithm provides acceptable performance and accuracy. Validation of the model was performed using data from full-scale experiments, which allowed to identify the weaknesses and advantages of the resulting system more accurately.