Modeling of ship maneuvering motion using neural networks

Weilin Luo , Zhicheng Zhang

Journal of Marine Science and Application ›› 2016, Vol. 15 ›› Issue (4) : 426 -432.

PDF
Journal of Marine Science and Application ›› 2016, Vol. 15 ›› Issue (4) : 426 -432. DOI: 10.1007/s11804-016-1380-8
Article

Modeling of ship maneuvering motion using neural networks

Author information +
History +
PDF

Abstract

In this paper, Neural Networks (NNs) are used in the modeling of ship maneuvering motion. A nonlinear response model and a linear hydrodynamic model of ship maneuvering motion are also investigated. The maneuverability indices and linear non-dimensional hydrodynamic derivatives in the models are identified by using two-layer feed forward NNs. The stability of parametric estimation is confirmed. Then, the ship maneuvering motion is predicted based on the obtained models. A comparison between the predicted results and the model test results demonstrates the validity of the proposed modeling method.

Keywords

ship maneuvering / response models / MMG model / system identification / neural networks

Cite this article

Download citation ▾
Weilin Luo, Zhicheng Zhang. Modeling of ship maneuvering motion using neural networks. Journal of Marine Science and Application, 2016, 15(4): 426-432 DOI:10.1007/s11804-016-1380-8

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Abkowitz MA. Measurement of hydrodynamic characteristic from ship maneuvering trials by system identification. Transactions of Society of Naval Architects and Marine Engineers, 1980, 88: 283-318

[2]

Bhattacharyya SK, Haddara MR. Parametric identification for nonlinear ship manoeuvring. Journal of Ship Research, 2006, 50(3): 197-207

[3]

Chen Y, Song Y, Chen M. Parameters identification for ship motion model based on particle swarm optimization. Kybernetes, 2010, 39(6): 871-880

[4]

Ebada A, Abdel-Maksoud M. Applying artificial intelligence (A.I.) to predict the limits of ship turning manoeuvres. Year Book of Shipbuilding Institute, 2005, 99: 132-139

[5]

Haddara MR, Wang Y. Parametric identification of maneuvering models for ships. International Shipbuilding Progress, 1999, 46(445): 5-27

[6]

Herrero ER, Gonzalez FJV. Two-step identification of non-linear manoeuvring models of marine vessels. Ocean Engineering, 2012, 53: 72-82

[7]

Hess D, Faller W, Lee J, Fu T, Ammeen E. Ship maneuvering simulation in wind and waves: a nonlinear time-domain approach using recursive neural networks. Proceedings of the 26th Symposium on Naval Hydrodynamics, 2006

[8]

Holzhüter T. Robust identification in an adaptive track controller for ships. Proceedings of the 3rd IFAC Symposium on Adaptive Systems in Control and Signal Processing, 1989, 275-280

[9]

IMO, 2002. Standards for ship manoeuvrability. Resolution MSC.137(76). International Maritime Organization, Lodon.

[10]

Källström CG, Åström KJ. Experiences of system identification applied to ship steering. Automatica, 1981, 17(1): 187-198

[11]

Lewis FL, Liu K, Yesildirek A. Neural net robot controller with guaranteed tracking performance. IEEE Transactions on Neural Networks, 1995, 6(3): 703-715

[12]

Luo WL, Moreira L, Guedes Soares C. Manoeuvring simulation of catamaran by using implicit models based on support vector machines. Ocean Engineering, 2014, 82: 150-159

[13]

Luo WL, Guedes Soares C, Zou ZJ. Parameter identification of ship manoeuvring model based on support vector machines and particle swarm optimization. Journal of Offshore Mechanics Arctic Engineering, 2016, 138(3): 031101-1

[14]

Moreira L, Guedes Soares C. Dynamic model of manoeuvrability using recursive neural networks. Ocean Engineering, 2003, 30(13): 1669-1697

[15]

Moreira L, Guedes Soares C. Comparison between manoeuvring trials and simulations with recursive neural networks. Ship Technology Research, 2003, 50: 77-84

[16]

Newman JN. Marine hydrodynamics, 1977, Cambridge, USA: M.I.T Press

[17]

Nomoto K, Tagushi T, Honda K, Hirano S. On steering qualities of ships. International Shipbuilding Progress, 1957, 4(35): 354-370

[18]

Qu ZH, Dawson DM. Robust tracking control of robot manipulators, 1995, Piscataway, USA: IEEE Press

[19]

Rajesh G, Bhattacharyya SK. System identification for nonlinear maneuvering of large tankers using artificial neural network. Applied Ocean Research, 2008, 30(4): 256-263

[20]

Sutulo S, Guedes Soares C. An algorithm for offline identification of ship manoeuvring mathematical models from free-running tests. Ocean Engineering, 2014, 79: 10-25

[21]

Van Amerongen J. Adaptive steering of ships -a model reference approach. Automatica, 1984, 20(1): 3-14

[22]

Yoon HK, Rhee KP. Identification of hydrodynamic derivatives in ship maneuvering equations of motion by estimation-before-modeling technique. Ocean Engineering, 2003, 30: 2379-2404

[23]

Zhou WW, Blanke M. Identification of a class of nonlinear state-space models using RPE techniques. IEEE Transactions on Automatic Control, 1989, 34(3): 312-316

AI Summary AI Mindmap
PDF

179

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/