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Mathematical Problems in Engineering
Volume 2016, Article ID 4650380, 9 pages
http://dx.doi.org/10.1155/2016/4650380
Research Article

Efficient Multivariable Generalized Predictive Control for Autonomous Underwater Vehicle in Vertical Plane

College of Automation, Harbin Engineering University, Harbin 150001, China

Received 6 July 2016; Accepted 23 October 2016

Academic Editor: Laurent Mevel

Copyright © 2016 Xuliang Yao and Guangyi Yang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. G. N. Roberts, “Trends in marine control systems,” Annual Reviews in Control, vol. 32, no. 2, pp. 263–269, 2008. View at Publisher · View at Google Scholar · View at Scopus
  2. Y. Nakamura and S. Savant, “Nonlinear tracking control of autonomous underwater vehicles,” in Proceedings of the IEEE International Conference on Robotics and Automation, vol. 3, pp. A4–A9, Nice, France, May 1992. View at Scopus
  3. Y. Xuliang, M. Lingwei, and W. Cunli, “On the motion control strategy of AUV to optimize the voyage resistance,” in Proceedings of the 34th Chinese Control Conference (CCC '15), pp. 4274–4279, July 2015. View at Publisher · View at Google Scholar · View at Scopus
  4. L. Yu, S. Liu, F. Liu, and H. Wang, “Energy optimization of the fin/rudder roll stabilization system based on the multi-objective genetic algorithm (MOGA),” Journal of Marine Science and Application, vol. 14, no. 2, pp. 202–207, 2015. View at Publisher · View at Google Scholar · View at Scopus
  5. Z. Liu and H. Jin, “Extended radiated energy method and its application to a ship roll stabilisation control system,” Ocean Engineering, vol. 72, pp. 25–30, 2013. View at Publisher · View at Google Scholar · View at Scopus
  6. H. Wang, L. Wang, and L. Pan, “Research on roll stabilizing based on energy optimization for autonomous surface vehicle,” Journal of Applied Mathematics, vol. 2014, Article ID 347589, 15 pages, 2014. View at Publisher · View at Google Scholar · View at Scopus
  7. X. Liang, X. Hua, L. Su, W. Li, and J. Zhang, “Energy conservation control strategy of autonomous underwater vehicle for ocean search,” Journal of Coastal Research, vol. 73, pp. 589–593, 2015. View at Publisher · View at Google Scholar · View at Scopus
  8. J. L. D. Dantas, J. J. da Cruz, and E. A. de Barros, “Study of autonomous underwater vehicle wave disturbance rejection in the diving plane,” Proceedings of the Institution of Mechanical Engineers Part M: Journal of Engineering for the Maritime Environment, vol. 228, no. 2, pp. 122–135, 2014. View at Publisher · View at Google Scholar · View at Scopus
  9. E. F. Camacho and C. B. Alba, Model Predictive Control, Springer Science & Business Media, 2013.
  10. Z. J. Tang, Q. B. He, S. A. Wang, and J. L. Shen, “An improved generalized predictive control for AUV yaw,” Advanced Materials Research, pp. 1709–1713, 2012. View at Google Scholar
  11. T. Geng and J. Zhao, “Generalized predictive control with constraints for autonomous underwater vehicle depth control,” in Proceedings of the International Conference on Modelling, Identification and Control (ICMIC '12), pp. 618–623, June 2012. View at Scopus
  12. Y. Xuliang and Y. Guangyi, “Constrained generalized predictive control for propulsion motor of autonomous underwater vehicle,” in Proceedings of the International Conference on Control, Automation and Information Sciences (ICCAIS '15), pp. 366–371, Changshu, China, October 2015. View at Publisher · View at Google Scholar
  13. D. P. Bertsekas, “Nonlinear Programming,” 1999.
  14. M. R. Katebi and M. A. Johnson, “Predictive control design for large-scale systems,” Automatica, vol. 33, no. 3, pp. 421–425, 1997. View at Publisher · View at Google Scholar · View at MathSciNet
  15. H. Ferreau, H. Bock, and M. Diehl, “An online active set strategy for fast parametric quadratic programming in MPC applications,” 2006.
  16. E. F. Camacho, “Constrained generalized predictive control,” IEEE Transactions on Automatic Control, vol. 38, no. 2, pp. 327–332, 1993. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  17. D. A. Wismer and R. Chattergy, Introduction to Nonlinear Optimization: A Problem Solving Approach, North-Holland, New York, NY, USA, 1978. View at MathSciNet
  18. M. Ćalasan, N. Šoć, V. Vujičić et al., “Review of marine current speed and power coefficient—mathematical models,” in Proceedings of the 4th Mediterranean Conference on Embedded Computing (MECO '15), June 2015. View at Publisher · View at Google Scholar
  19. J. P. J. Avila and J. C. Adamowski, “Experimental evaluation of the hydrodynamic coefficients of a ROV through Morison's equation,” Ocean Engineering, vol. 38, no. 17-18, pp. 2162–2170, 2011. View at Publisher · View at Google Scholar · View at Scopus
  20. D. W. Clarke, C. Mohtadi, and P. S. Tuffs, “Generalized predictive control—Part I. The basic algorithm,” Automatica, vol. 23, no. 2, pp. 137–148, 1987. View at Publisher · View at Google Scholar · View at Scopus
  21. A. I. Field, Simulation, modelling, and control of a near-surface underwater vehicle, 2000.
  22. T. I. Fossen, A Guidance and Control of Ocean Vehicles, 1994.
  23. L. Wang, Model Predictive Control System Design and Implementation Using MATLAB®, Springer Science & Business Media, 2009. View at Publisher · View at Google Scholar