Two-step identification of non-linear manoeuvring models of marine vessels

Abstract This paper presents the identification of non-linear ship manoeuvring models. It is a gray box approach in which some of the parameters of the models are known, and where a novel identification scheme for non-linear manoeuvring models based on two steps is proposed. In the first step, the structure of the model is selected using the stepwise method, and the parameters which present greater uncertainty are estimated. In the second step, a refinement of the estimates in the first step is carried out using a non-linear prediction error method with the unscented Kalman filter. As an application example, we consider a modern high-speed trimaran ferry using a full-scale trial and simulated data sets.

[1]  Tristan Perez,et al.  Parameter estimation of thrust models of uninhabited airborne systems , 2010 .

[2]  H. W. Sorenson,et al.  Kalman filtering : theory and application , 1985 .

[3]  Eugene A. Morelli,et al.  Aircraft system identification : theory and practice , 2006 .

[4]  Key Pyo Rhee,et al.  Identification of hydrodynamic coefficients in ship maneuvering equations of motion by Estimation-Before-Modeling technique , 2003 .

[5]  S. K. Bhattacharyya,et al.  A FREQUENCY DOMAIN SYSTEM IDENTIFICATION METHOD FOR LINEAR SHIP MANEUVERING , 2005 .

[6]  Donghoon Kang,et al.  Prediction method of hydrodynamic forces acting on the hull of a blunt-body ship in the even keel condition , 2007 .

[7]  Baha M. Suleiman,et al.  Identification of Finite-Degree-of-Freedom Models for Ship Motions , 2000 .

[8]  Jeffrey K. Uhlmann,et al.  New extension of the Kalman filter to nonlinear systems , 1997, Defense, Security, and Sensing.

[9]  William H. Press,et al.  The Art of Scientific Computing Second Edition , 1998 .

[10]  M A Abkowitz,et al.  MEASUREMENT OF HYDRODYNAMIC CHARACTERISTICS FROM SHIP MANEUVERING TRIALS BY SYSTEM IDENTIFICATION , 1980 .

[11]  Thor I. Fossen,et al.  Marine Control Systems Guidance, Navigation, and Control of Ships, Rigs and Underwater Vehicles , 2002 .

[12]  Asgeir J. Sørensen,et al.  Identification of Dynamically Positioned Ships , 1995 .

[13]  Gengshen Liu,et al.  Application of EKF technique to ship resistance measurement , 1993, Autom..

[14]  Job van Amerongen,et al.  Adaptive steering of ships - A model reference approach , 1982, Autom..

[15]  Petre Stoica,et al.  Decentralized Control , 2018, The Control Systems Handbook.

[16]  Marc Vantorre,et al.  The Manoeuvring Committee - Final Report and Recommendations to the 23rd ITTC. , 1999 .

[17]  A. Atkinson.  Subset Selection in Regression , 1992 .

[18]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[19]  Gyeong Joong Lee,et al.  Estimation of the Roll Hydrodynamic Moment Model of a Ship by Using the System Identification Method and the Free Running Model Test , 2007, IEEE Journal of Oceanic Engineering.

[20]  K K Fedyaevsky,et al.  CONTROL AND STABILITY IN SHIP DESIGN , 1964 .

[21]  Manuel Haro Casado,et al.  Identification of nonlinear ship model parameters based on the turning circle test , 2007 .

[22]  Jeffrey K. Uhlmann,et al.  Unscented filtering and nonlinear estimation , 2004, Proceedings of the IEEE.

[23]  Karl Johan Åström.  Maximum likelihood and prediction error methods , 1980, Autom..

[24]  A. Lloyd,et al.  Seakeeping: Ship Behaviour in Rough Weather , 1998 .

[25]  Rudolph van der Merwe,et al.  The unscented Kalman filter for nonlinear estimation , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[26]  Andrew Ross,et al.  Nonlinear Manoeuvring Models for Ships: A Lagrangian Approach , 2008 .

[27]  Simon J. Julier,et al.  The scaled unscented transformation , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[28]  Tristan Perez,et al.  Ship Motion Control: Course Keeping and Roll Stabilisation Using Rudder and Fins , 2005 .

[29]  Andrew Ross,et al.  IDENTIFICATION OF NONLINEAR VISCOUS DAMPING FOR MARINE VESSELS , 2006 .

[30]  Odd M. Faltinsen,et al.  Sea loads on ships and offshore structures , 1990 .

[31]  M A Abkowitz,et al.  LECTURES ON SHIP HYDRODYNAMICS--STEERING AND MANOEUVRABILITY , 1964 .

[32]  S. K. Bhattacharyya,et al.  Parametric Identification for Nonlinear Ship Maneuvering , 2006 .

[33]  Fei Chun Ma,et al.  Real time parameters identification of ship dynamic using the extended Kalman filter and the second order filter , 2003, Proceedings of 2003 IEEE Conference on Control Applications, 2003. CCA 2003..

[34]  Tristan Perez,et al.  A novel manoeuvering model based on low-aspect-ratio lift theory and Lagrangian mechanics , 2007 .

[35]  Thor I. Fossen,et al.  Practical aspects of frequency-domain identification of dynamic models of marine structures from hydrodynamic data , 2011 .

[36]  Sheng Liu,et al.  Investigation of steering dynamics ship model identification based on PSO-LSSVR , 2008, 2008 2nd International Symposium on Systems and Control in Aerospace and Astronautics.

[37]  Sy-Miin Chow,et al.  An Unscented Kalman Filter Approach to the Estimation of Nonlinear Dynamical Systems Models , 2007, Multivariate behavioral research.

[38]  Marc Vantorre,et al.  Proceedings of the 21st International Towing Tank Conference, ITTC'96: Report of the Manoeuvrability Committee , 1996 .

[39]  G. B. Kang,et al.  A study on system identification and anti-rolling system design of a ship with the flap , 2003, SICE 2003 Annual Conference (IEEE Cat. No.03TH8734).

[40]  C. Guedes Soares,et al.  Dynamic model of manoeuvrability using recursive neural networks , 2003 .

[41]  Ayman B. Mahfouz.  Identification of the nonlinear ship rolling motion equation using the measured response at sea , 2004 .

[42]  Tristan Perez,et al.  Validation of a 4DOF Manoeuvring Model of a High-speed Vehicle- Passenger Trimaran , 2007 .

[43]  P. Protzel,et al.  Using the Unscented Kalman Filter in Mono-SLAM with Inverse Depth Parametrization for Autonomous Airship Control , 2007, 2007 IEEE International Workshop on Safety, Security and Rescue Robotics.

[44]  L. Wasserman.  All of Nonparametric Statistics , 2005 .