Estimation of hydrodynamic coefficients for an AUV using nonlinear observers

Hydrodynamic coefficients strongly affect the dynamic performance of an autonomous underwater vehicle. Although these coefficients are generally obtained experimentally such as through the planar-motion-mechanism (PMM) test, the measured values are not completely reliable because of experimental difficulties and errors involved. Another approach by which these coefficients can be obtained is the observer method, in which a model-based estimation algorithm predicts the coefficients. In this paper, the hydrodynamic coefficients are estimated using two nonlinear observers - a sliding mode observer and an extended Kalman filter. Their performances are evaluated by comparing the estimated coefficients obtained from the two observer methods with the values as determined from the PMM test. By using the estimated coefficients, a sliding mode controller is constructed for the diving and steering maneuver. It is demonstrated that the controller with the estimated values maintains the desired depth and path with sufficient accuracy.

[1]  Wei-yuan Hwang Application of system identification to ship maneuvering , 1980 .

[2]  Debabrata Sen A Study on Sensitivity of Maneuverability Performance on the Hydrodynamic Coefficients for Submerged Bodies , 2000 .

[3]  J. Slotine,et al.  On Sliding Observers for Nonlinear Systems , 1986, 1986 American Control Conference.

[4]  S. Chiaverini,et al.  Tracking control for underwater vehicle-manipulator systems with velocity estimation , 2000, IEEE Journal of Oceanic Engineering.

[5]  T.I. Fossen,et al.  Nonlinear output feedback control of underwater vehicle propellers using feedback form estimated axial flow velocity , 2000, IEEE Journal of Oceanic Engineering.

[6]  R. L. Wernli AUVs-a technology whose time has come , 2002, Proceedings of the 2002 Interntional Symposium on Underwater Technology (Cat. No.02EX556).

[7]  A. J. Healey,et al.  Adaptive sliding mode control of autonomous underwater vehicles in the dive plane , 1990 .

[8]  Jong-Won Park,et al.  Discrete-time quasi-sliding mode control of an autonomous underwater vehicle , 1999 .

[9]  A. J. Healey,et al.  Multivariable sliding mode control for autonomous diving and steering of unmanned underwater vehicles , 1993 .

[10]  Laura R. Ray,et al.  Nonlinear Tire Force Estimation and Road Friction Identification: Simulation and Experiments, , 1997, Autom..

[11]  Jay A. Farrell,et al.  Issues in the implementation of an indirect adaptive control system , 1993 .

[12]  M. Boutayeb,et al.  Convergence analysis of the extended Kalman filter used as an observer for nonlinear deterministic discrete-time systems , 1997, IEEE Trans. Autom. Control..

[13]  Junku Yuh,et al.  Modeling and control of underwater robotic vehicles , 1990, IEEE Trans. Syst. Man Cybern..

[14]  J. K. Hedrick,et al.  Estimation of Vehicle Shaft Torque Using Nonlinear Observers , 1992 .

[15]  Euan McGookin,et al.  Reconfigurable sliding mode control for submarine manoeuvring , 2001, MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No.01CH37295).