Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-11T03:47:54.120Z Has data issue: false hasContentIssue false
  • English
  • Français

An Autopilot Based on a Local Control Network Design for an Unmanned Surface Vehicle

Published online by Cambridge University Press:  12 March 2012

SK Sharma ,
W Naeem  and
R Sutton
SK Sharma*
Affiliation:
(School of Marine Science and Engineering, Plymouth University, Plymouth)
W Naeem
Affiliation:
(School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast)
R Sutton
Affiliation:
(School of Marine Science and Engineering, Plymouth University, Plymouth)
*
(E-mail: sanjay.sharma@plymouth.ac.uk)
Get access Rights & Permissions [Opens in a new window]

Abstract

Over recent years, a number of marine autopilots designed using linear techniques have underperformed owing to their inability to cope with nonlinear vessel dynamics. To this end, a new design framework for the development of nonlinear autopilots is proposed. Local Control Networks (LCNs) can be used in the design of nonlinear control systems. In this paper, a LCN approach is taken in the design of a nonlinear autopilot for controlling the nonlinear yaw dynamics of an unmanned surface vehicle known as Springer. It is considered the approach is the first of its kind to be used in marine control systems design. Simulation results are presented and the performance of the nonlinear autopilot is compared with that of an existing Springer Linear Quadratic Gaussian (LQG) autopilot using standard system performance criteria. From the results it can be concluded the LCN autopilot out-performed that based on LQG techniques in terms of the selected criteria. Also it provided more energy saving control strategies and would thereby increase operational duration times for the vehicle during real-time missions.

Keywords

Unmanned Surface VehicleAutopilot DesignLinear Quadratic Gaussian ControlLocal Control Network
Type
Research Article
Information
The Journal of Navigation , Volume 65 , Issue 2 , April 2012 , pp. 281 - 301
Copyright
Copyright © The Royal Institute of Navigation 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Brown, M. D., Lightbody, G. and Irwin, G. W. (1997). Non-linear Internal Model Control using Local Model Networks. IEE Proceedings on Control Theory and Applications, 144, 505–514.CrossRefGoogle Scholar
Burl, J. B. (1999). Linear Optimal Control, H2 and H∞ Methods. Addison-Wesley Longman Inc.Google Scholar
Caccia, M., Bibuli, M., Bono, R., Bruzzone, Ga., Bruzzone, Gi. and Spirandelli, E. (2007). Unmanned Surface Vehicle for Coastal and Protected Waters Applications: The Charlie Project. Marine Technology Society Journal, 41, 62–71.CrossRefGoogle Scholar
Fossen, T. I. (2000). A Survey of Nonlinear Ship Control: From Theory to Practice. Proceedings of the 5th IFAC Conference on Manoeuvring and Control of Marine Craft, Aalborg, Denmark.CrossRefGoogle Scholar
Fossen, T. I. (2011). Handbook of Marine Craft Hydrodynamics and Motion Control. John Wily and Sons.CrossRefGoogle Scholar
Franklin, G.F., Powell, J. D. and Workman, M. (1998). Digital Control of Dynamic Systems. 3rd Edition, Addison-Wesley Longman Inc.Google Scholar
Holzhuter, T. and Schultze, R. (1996). Operating Experience with a High Precision Track Controller for Commercial Ships. Control Engineering Practice, Vol 4, 343–350.CrossRefGoogle Scholar
Johansen, T. A. and Foss, B. A. (1995). Semi-Empirical Modelling of Nonlinear Dynamic Systems Through Identification of Operating Regimes and Local Models. Neural Network Engineering in Dynamic Systems, 105–126.CrossRefGoogle Scholar
Ljung, L. (1999). System Identification: Theory for the User. 2nd Edition. Prentice Hall Inc., New Jersey.Google Scholar
Majohr, J., Buch, T. and Korte, C. (2000). Navigation and Automatic Control of the Measuring Dolphin (Messin™). Proceedings of 5th IFAC Conference on Manoeuvring and Control of Marine Craft, Aalborg, Denmark.CrossRefGoogle Scholar
Michalewicz, Z. (1996). Genetic Algorithms+Data Structures=Evolution Programs. 3rd Edition, Springer-Verlag, New York.CrossRefGoogle Scholar
Minoriski, N. (1922). Directional Stability of Automatic Steered Bodies. Journal of the American Society of Naval Engineer, 34(2), 280–309.CrossRefGoogle Scholar
Moreira, L. and Soares, G. C. (2005). Design of Robust Steering Autopilot for Ships. Proceedings of the 12th International Congress of the International Maritime Association of the Mediterranean, Lisbon, Portugal.Google Scholar
Naeem, W., Xu, T., Sutton, R. and Tiano, A. (2008). The Design of a Navigation, Guidance, and Control System for an Unmanned Surface Vehicle for Environmental Monitoring. Proceedings of the Institute of Mechanical Engineers Part M: Journal of Engineering for the Maritime Environment, 222 M2, 67–80.Google Scholar
Ogata, K. (2002). Modern Control Engineering. 4th Edition, Prentice-Hall Inc.Google Scholar
Rippin, D. W. T. (1989). Control of Batch Processes. Proceedings of the 3rd IFAC DYCORD+'89 Symposium, Maastrict, Netherlands.CrossRefGoogle Scholar
Sharma, S. K., McLoone, S. and Irwin, G. W. (2005). Genetic Algorithms for Local Controller Network Construction. Proceedings of the IEE, Control Theory & Application, 152, 587–597.CrossRefGoogle Scholar
Sharma, S. K., McLoone, S. and Irwin, G. W. (2002). Genetic Algorithms for Local Model and Local Controller Network Design. Proceedings of the American Control Conference, Anchorage, USA.CrossRefGoogle Scholar
Sivanandam, S. N. and Deepa, S. N. (2008). Introduction to Genetic Algorithms. Springer-Verlag, Berlin.Google Scholar
Sperry, E. A. (1922). Automatic Steering. Trans Society of Naval Architects and Marine Engineers, 53–61.Google Scholar
Sperry Gyroscope Company (2011). A Short History of Sperry Marine. www.sperrymarine.northropgrumman.com/Company-Information/Corporate-History/Sperry-History/ accessed 27 September 2011.Google Scholar
Townsend, S., Lightbody, G., Brown, M. D. and Irwin, G. W. (1998). Nonlinear Dynamic Matrix Control using Local Model Networks. Trans Inst MC, 20, 47–56.CrossRefGoogle Scholar
Tran, V. T., Nguyen, H. T., Hoang, T. X., Nguyen, T. M. H., Cu, X.-T. and Nguyen, V. P. (2004). An Optimal Autopilot for Ships using a Regressive Exogenous Model. Proceedings of the International Symposium on Communications and Information Technologies, Sapporo, Japan.Google Scholar
Yan, R. J., Pang, S., Sun, H. B. and Pang, Y. J. (2010). Development and Missions of Unmanned Surface Vehicle. Journal of Marine Science and Application, 9, 451–457.CrossRefGoogle Scholar