The inherent strongly nonlinear and coupling performance of the Autonomous Underwater Vehicles （AUV）, maneuvering motion in the diving plane determines its difficulty in parametric identification. The motion parameters in diving plane are obtained by executing the Zigzag-like motion based on a mathematical model of maneuvering motion. A separate identification method is put forward for parametric identification by investigating the motion equations. Support vector machine is proposed to estimate the hydrodynamic derivatives by analyzing the data of surge, heave and pitch motions. Compared with the standard coefficients, the identified parameters show the validation of the proposed identification method. Sensitivity analysis based on numerical simulation demonstrates that poor sensitive derivative gives bad estimation results. Finally the motion simulation is implemented based on the dominant sensitive derivatives to verify the reconstructed model.
By analyzing the data of longitudinal speed, transverse speed and rudder angle etc. in the simulated 10°/10°zigzag test, the hydrodynamic derivatives in the Abkowitz model for ship manoeuvring motion are identified by using e-Support Vector Regression （ε -SVR）. To damp the extent of parameter drift, a series of random numbers are added into the training samples to reconstruct the training samples. The identification results of the hydrodynamic derivatives are compared with the Planar Motion Mechanism （PMM） test results to verify the identification method. By using the identified Abkowitz model, 20°/20° zigzag test is numerically simulated. The simulated results are compared with those obtained by using the Abkowitz model where the hydrodynamic derivatives are obtained from PMM tests. The agreement is satisfactory, which shows that the regressive Abkowitz model has a good generalization performance.
