A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel

Bańka, Stanisław; Brasel, Michał; Dworak, Paweł; Jaroszewski, Krzysztof

doi:10.1515/amcs-2015-0063

Abstract

The paper presents algorithms for parameter identification of linear vessel models being in force for the current operating point of a ship. Advantages and disadvantages of gradient and genetic algorithms in identifying the model parameters are discussed. The study is supported by presentation of identification results for a nonlinear model of a drilling vessel.

References

Al Seyab, R. and Cao, Y. (2008). Nonlinear system identification for predictive control using continuous time recurrent neural networks and automatic differentiation, Journal of Process Control18(6): 568–581.10.1016/j.jprocont.2007.10.012
Search in Google Scholar
Anil Ari Guner, H., Yuksel, Y. and Cevik, E.O. (2013). Estimation of wave parameters based on nearshore wind-wave correlations, Ocean Engineering63: 52–62.10.1016/j.oceaneng.2013.01.023
Search in Google Scholar
Aström, K. and Källström, C. (1976). Identification of ship steering dynamics, Automatica12(1): 9–22.10.1016/0005-1098(76)90064-9
Search in Google Scholar
Aström, K. and Källström, C. (1981). Experiences of system identification applied to ship steering, Automatica17(1): 187–198.10.1016/0005-1098(81)90094-7
Search in Google Scholar
Bańka, S. (2007). Multivariable Control Systems: A Polynomial Approach, Monographs of the Committee of Automation and Robotics, Polish Academy of Sciences, Szczecin University of Technology Press, Szczecin, (in Polish).
Search in Google Scholar
Bańka, S., Dworak, P., Brasel, M. and Latawiec, K.J. (2010). Switched structure of linear MIMO controllers for positioning of a drillship on a sea surface, Proceedings of the 15th International Conference on Methods and Models in Automation and Robotics, MMAR 2010, Międzyzdroje, Poland, pp. 249–254.
Search in Google Scholar
Bańka, S., Dworak, P. and Jaroszewski, K. (2013). Linear adaptive structure for control of a nonlinear MIMO dynamic plant, International Journal of Applied Mathematics and Computer Science23(1): 47–63, DOI: 10.2478/amcs-2013-0005.10.2478/amcs-2013-0005
Search in Google Scholar
Barth, S. and Eecen, P. (2006). Description of the relation of wind, wave and current characteristics at the offshore wind farm Egmond aan Zee, Technical report, NoordzeeWind, IJmuiden.
Search in Google Scholar
Billings, S. (2013). Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-temporal Domains, Wiley, Chichester.10.1002/9781118535561
Search in Google Scholar
Bredmose, H., Larsen, S., Matha, D., Rettenmeier, A., Marino, E. and Seattran, L. (2012). Collation of offshore wind-wave dynamics, Technical report, Marine Renewables Infrastructure Network.
Search in Google Scholar
Chen, W., Yan, K., Shi, G. and Lu, H. (2008). A new swarm intelligence and parameter identification of hydrodynamic forces acting on axis-symmetric body exiting water obliquely, Journal of Ship Mechanics12(2): 204–210.
Search in Google Scholar
Dai, Y., Li, Y. and Song, J. (2012). Parameter identification of ship lateral motions using evolution particle swarm optimization, Proceedings of the 5th International Joint Conference on Computational Sciences and Optimization, CSO 2012, Harbin, China, pp. 797–801.
Search in Google Scholar
Dai, Y., Zhao, X. and Liu, L. (2010). Parameter identification of ship longitudinal motions using continuous ant colony algorithm with period searching, Journal of Ship Mechanics14(8): 872–878.
Search in Google Scholar
Dworak, P. and Brasel, M. (2013). Improving quality of regulation of a nonlinear MIMO dynamic plant, Elektronika Ir Elektrotechnika19(7): 3–6.10.5755/j01.eee.19.7.5153
Search in Google Scholar
Fossen, T.I. (1994). Guidance and Control of Ocean Vehicles, John Wiley and Sons, Chichester.
Search in Google Scholar
Fossen, T.I. (2011). Handbook of Marine Craft Hydrodynamics and Motion Control, John Wiley and Sons, Chichester.10.1002/9781119994138
Search in Google Scholar
Herrero, E. and González, F.V. (2012). Two-step identification of non-linear manoeuvring models of marine vessels, Ocean Engineering53: 72–82.10.1016/j.oceaneng.2012.07.010
Search in Google Scholar
Kondo, J., Fujinawa, Y. and Naito, G. (1972). Wave-induced wind fluctuation over the sea, Journal of Fluid Mechanics51(4): 751–771.10.1017/S002211207200134X
Search in Google Scholar
Lewis, E.V. (1989). Principles of Naval Architecture, Volume III: Motions in Waves and Controllability, Society of Naval Architects and Marine Engineers, Alexandria, VA.
Search in Google Scholar
Ljung, L. (2001). System Identification. Theory for the User, Prentice-Hall, Englewood Cliffs, NJ.
Search in Google Scholar
Mahfouz, A. and Haddara, M. (2003). Effect of the damping and excitation on the identification of the hydronamic parameters for an underwater robotic vehicle, Ocean Engineering30(8): 1005–1025.10.1016/S0029-8018(02)00080-X
Search in Google Scholar
Mzyk, G. (2013). Nonparametric instrumental variables for identification of block-oriented systems, International Journal of Applied Mathematics and Computer Science23(3): 521–537, DOI: 10.2478/amcs-2013-0040.10.2478/amcs-2013-0040
Search in Google Scholar
Nelles, O. (2001). Nonlinear System Identification, Springer-Verlag, Berlin/Heidelberg.10.1007/978-3-662-04323-3
Search in Google Scholar
Orjuela, R., Marx, B., Ragot, J. and Maquin, D. (2013). Nonlinear system identification using heterogeneous multiple models, International Journal of Applied Mathematics and Computer Science23(1): 103–115, DOI: 10.2478/amcs-2013-0009.10.2478/amcs-2013-0009
Search in Google Scholar
Padilla, A. and Yuz, J. (2013). Continuous-time system identification of a ship on a river, Proceedings of the 52nd Annual Conference on Decision and Control, CDC 2013, Firenze, Italy, pp. 4553–4558.
Search in Google Scholar
Revestido, E., Velasco, F., Zamanillo, I., Lopez, E. and Moyano, E. (2011). Parameter estimation of ship linear maneuvering models, Proceedings of IEEE OCEANS 2011, Santander, Spain, pp. 1–8.
Search in Google Scholar
Skjetne, R., Smogeli, Ø. and Fossen, T. (2004). A nonlinear ship manoeuvering model: Identification and adaptive control with experiments for a model ship, Modeling, Identification and Control25(1): 3–27.10.4173/mic.2004.1.1
Search in Google Scholar
Tran Khanh, T., Ouahsine, A., Naceur, H. and Wassifi, K.E. (2013). Assessment of ship manoeuvrability by using a coupling between a nonlinear transient manoeuvring model and mathematical programming techniques, Journal of Hydrodynamics B25(5): 788–804.10.1016/S1001-6058(13)60426-6
Search in Google Scholar
Velasco, F., Herrero, E., Lopez, L. and Moyano, E. (2013). Identification for a heading autopilot of an autonomous in-scale fast ferry, IEEE Journal of Oceanic Engineering38(2): 263–274.10.1109/JOE.2012.2227175
Search in Google Scholar
Wang, Y., Meng, H., Liu, Z.-L. and Yu, R.-T. (2011). On-line of modeling ship manoeuvring motion by using least squares support vector machines, Proceedings of the IEEE 18th International Conference on Industrial Engineering and Engineering Management, Changchun, China, pp. 1712–1716.
Search in Google Scholar
Wise, D.A. and English, J.W. (1975). Tank and wind tunnel tests for a drill-ship with dynamic position control, Offshore Technology Conference, Dallas, TX, USA, pp. 103–118.
Search in Google Scholar
Yoon, H. and Rhee, K. (2003). Identification of hydrodynamic coefficients in ship maneuvering equations of motion by estimation-before-modeling technique, Ocean Engineering30(18): 2379–2404.10.1016/S0029-8018(03)00106-9
Search in Google Scholar
Yoon, H., Son, N.S. and Lee, C.M. (2004). Estimation of roll related hydrodynamic coefficients through the free running model tests, Proceedings of IEEE TECHNO-OCEAN’04, Kobe, Japan, pp. 1086–1092.
Search in Google Scholar
Yoon, H., Son, N. and Lee, G. (2007). Estimation of the roll hydrodynamic moment model of a ship by using the system identification method and the free running model test, IEEE Journal of Oceanic Engineering32(4): 798–806.10.1109/JOE.2007.909840
Search in Google Scholar
Zhang, H.-G. and Zou, Z.-J. (2011). Identification of abkowitz model for ship manoeuvring motion using ε-support vector regression, Journal of Hydrodynamics B23(3): 353–360.10.1016/S1001-6058(10)60123-0
Search in Google Scholar
Zhang, Z., Li, X., Yang, L. and Wu, G.Y. (2010). Parameter identification method for ship swaying motion differential equations, Proceedings of the 3rd International Joint Conference on Computational Science and Optimization, CSO 2010, Huangshan, Anhui, China, pp. 205–208.
Search in Google Scholar

A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel

Abstract

Paradigm

My account