ANALYSIS OF IMPACT of SHIP model parameters on changes of control quality index in ship dynamic positioning system - Publication - MOST Wiedzy

Search

ANALYSIS OF IMPACT of SHIP model parameters on changes of control quality index in ship dynamic positioning system

Abstract

In this work there is presented an analysis of impact of ship model parameters on changes of control quality index in a ship dynamic positioning system designed with the use of a backstepping adaptive controller. Assessment of the impact of ship model parameters was performed on the basis of Pareto-Lorentz curves and ABC method in order to determine sets of the parameters which have either crucial, moderate or low impact on objective function. Simulation investigations were carried out with taking into account integral control quality indices.

Citations

  • 0

    CrossRef

  • 0

    Web of Science

  • 0

    Scopus

Details

Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
Polish Maritime Research no. 26, pages 6 - 14,
ISSN: 1233-2585
Language:
English
Publication year:
2019
Bibliographic description:
Niksa-Rynkiewicz T., Witkowska A.: ANALYSIS OF IMPACT of SHIP model parameters on changes of control quality index in ship dynamic positioning system// Polish Maritime Research. -Vol. 26, nr. 1(101) (2019), s.6-14
DOI:
Digital Object Identifier (open in new tab) 10.2478/pomr-2019-0001
Bibliography: test
  1. Boulkroune, A., N. Bounar, M. M'Saad, M. Farza: Indirect adaptive fuzzy control scheme based on observer for nonlinear systems: A novel SPR-filter approach, Neurocomputing. 135, 2014 pp. 378-387. open in new tab
  2. Buhmann, M.D.: Radial basis functions: theory and implementations, Cambridge University Press 2003. open in new tab
  3. Chan, A.K., G.A. Becus: Online adaptation of RBF centers for adaptive control, in: Proceedings of 1995 American Control Conference -ACC'95, American Autom Control Council, 1995 pp. 3770-3774. open in new tab
  4. Cover, T.M.: Geometrical and Statistical Properties of Systems of Linear Inequalities with Applications in Pattern Recognition, IEEE Transactions on Electronic Computers 1965, pp. 326-334. open in new tab
  5. Cpałka, K.: Design of Interpretable Fuzzy Systems, Springer 2017. open in new tab
  6. Du, J., X. Hu, H. Liu, C.L.P. Chen: Adaptive robust output feedback control for a marine dynamic positioning system based on a high-gain observer, IEEE Transactions on Neural Networks and Learning Systems. 26, 2015, pp. 2775-2786. open in new tab
  7. Fossen, T.I., S.P. Berge: Nonlinear vectorial backstepping design for global exponential tracking of marine vessels in the presence of actuator dynamics, in: Proceedings of the 36th IEEE Conference on Decision and Control, IEEE, 1998, pp. 4237-4242. open in new tab
  8. Kang Y., Li D., Lao D.: Performance Robustness Comparison of Active Disturbance Rejection Control and Adaptive Backstepping Sliding Mode Control. In: Xiao T., Zhang L., Fei M. (eds) AsiaSim 2012. AsiaSim 2012. Communications in Computer and Information Science, vol 324. Springer, Berlin, Heidelberg open in new tab
  9. Katebi, M.R., M.J. Grimble, Y. Zhang: H∞ robust control design of dynamic ship positioning, IEE Process Control Theory Application. 144, 1997, pp. 110-120. open in new tab
  10. Krstić, M., I. Kanellakopoulos, P. Kokotović: Nonlinear and adaptive control design, Wiley 1995.
  11. Kuczkowski Ł., Śmierzchalski R. (2017) Path planning algorithm for ship collisions avoidance in environment with changing strategy of dynamic obstacles. In: Mitkowski W., Kacprzyk J., Oprzędkiewicz K., Skruch P. (eds) Trends in Advanced Intelligent Control, Optimization and Automation. KKA 2017. Advances in Intelligent Systems and Computing, vol 577. Springer, Cham, pp. 641-650. open in new tab
  12. Kwan, C., F.L. Lewis: Robust backstepping control of nonlinear systems using neural networks, Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions Vol. 30, No.6, 2000, pp. 753-766. open in new tab
  13. Linkens, D.A., Mahfouf, M. Abood, M.: Self-adaptive and self-organising control applied to nonlinear multivariable anesthesia: a comparative model-based study, IEE Proceedings-D, vol. 139, No. 4, July 1992, pp. 381-394 open in new tab
  14. Lisowski, J.: Game control methods in avoidance of ships collisions, Polish Maritime Research, No. 19, 2012, pp. 3-10. open in new tab
  15. Lisowski, J., A. Lazarowska: The radar data transmission to computer support system of ship safety, Solid State Phenomena. 196, 2013, pp. 95-101. open in new tab
  16. Mingyu, F., X. Yujie, Z. Li: Bio-inspired Trajectory Tracking Algorithm for Dynamic Positioning Ship with System Uncertainties, Proceedings of the 35th Chinese Control Conference, 2016, pp. 4562-4566.
  17. Niksa-Rynkiewicz,T.,Szłapczyński R.: A framework of a ship domain -based near-miss detection method using Mamdani neuro-fuzzy classification, Polish Maritime Research, SI (97), 2018, vol. 25, pp. 14-21.
  18. Orr, M.J.L.: Introduction to Radial Basis Function Networks, 1996. open in new tab
  19. Sorensen, A.: A survey of dynamic positioning control systems, Annual Reviews in Control, 35, 2011, pp. 123-136. open in new tab
  20. Swaroop, D., J.K. Hedrick, P.P. Yip, J.C. Gerdes: Dynamic surface control for a class of nonlinear systems, IEEE Transactions on Automatic Control. 45, 2000, pp. 1893-1899. open in new tab
  21. Szczypta J., Przybył A., Cpałka K. (2013) Some Aspects of Evolutionary Designing Optimal Controllers. In: Rutkowski L., Korytkowski M., Scherer R., Tadeusiewicz R., Zadeh L.A., Zurada J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2013. Lecture Notes in Computer Science, vol 7895. Springer, Berlin, Heidelberg. open in new tab
  22. Szlapczynski, R., J. Szlapczynska: Customized crossover in evolutionary sets of safe ship trajectories, International Journal of Applied Mathematics and Computer Science. 22, 2012. open in new tab
  23. Tannuri, E.A., A.C. Agostinho, H.M. Morishita, L. Moratelli: Dynamic positioning systems: An experimental analysis of sliding mode control, Control Engineering Practice. 18, 2010, pp. 1121-1132. open in new tab
  24. Witkowska, A., R. Śmierzchalski: Adaptive Dynamic Control Allocation for Dynamic Positioning of Marine Vessel Based on Backstepping Method and Sequential Quadratic Programming. Ocean Engineering 163, 2018, pp. 570-582. open in new tab
  25. Witkowska, A., T. Niksa-Rynkiewicz: Motion control of dynamically positioned unit by using backstepping method and artificial neural networks, to be published in Polish Maritime Research. open in new tab
  26. Yang, Y., J. Du, G. Li, W. Li, C. Guo: Dynamic Surface Control for Nonlinear Dynamic Positioning System of Ship, in: Advances in Intelligent and Soft Computing, Springer, Berlin, Heidelberg, 2012, pp. 237-244. open in new tab
  27. Ye, L., Zong, Q., Zhang, X.: Cascade Disturbance Rejection Control of the Uncertain Nonlinear Systems with Nonlinear Parameterization, Proceedings of the 34 th Chinese Control Conference, July 28-30, 2015, Hangzhou, China, pp. 991-996.
  28. Wei W., Donghai L., Jing W.: Adaptive Control for a Non- minimum Phase Hypersonic Vehicle Model. American Control Conference (ACC) Washington, DC, USA, June 17-19, 2013.
  29. Tykocki J., Jordan A., Surowik D.: Pareto -ABC Analysis of Temperature Field in High Voltage Three-Phase Cable Systems. Electrical Review, No. 5, (2014) R 91, pp. 107-112. open in new tab
Verified by:
Gdańsk University of Technology

seen 63 times

Recommended for you

Meta Tags