Open Access Open Access  Restricted Access Subscription Access

Model Predictive Control for Autonomous Underwater Vehicle

Agus Budiyono


The paper presents a new approach to the control of an autonomous underwater vehicle (AUV Squid) by using model predictive. The method is considered suitable for underwater vehicles characterized by sluggish dynamics and operation environment with unstructured uncertainty. In addition, the ability of the method to handle constraints inherent in the control inputs of AUV is appropriately exploited. Overall effectiveness of the method is evaluated for the improvement of the existing PID controller based on direct tuning.

Full Text:



Feijun Song and S.M. Smith, Design of sliding mode fuzzy controllers for an autonomous underwater vehicle without system model, OCEANS 2000 MTS/IEEE Conference and Exhibition, Volume 2, 11-14 Sept. 2000, pp.835 – 840

Feijun Song, Edgar An and Samuel Smith, “Design of robust nonlinear controllers for autonomous underwater vehicles with comparison of simulated and at-sea test data”, Journal of Vibration and Control, vol. 8 pp. 189—217, 2002

H.S. Kim, Y.K. Shin, Expanded Adaptive Fuzzy Sliding Mode Controller using Expert Knowledge and Fuzzy Basis Function Expansion for UFV Depth

Control, Journal of Ocean Engineering, 2007, Vol.34, pp.1080-1088

W.M. Bessa, M.S. Dutra, E. Kreuzer, Depth Control of Remotely Operated Underwater Vehicles using an Adaptive Fuzzy Sliding Mode Controller, Journal of Robotics and Autonomous System, 2007

J. Yuh, “A Neural Net Controller For Underwater Robotic Vehicles,” IEEE Journal of Oceanic Engineering, vol.15, no.3, pp.161-166, 1990.

Ishii, K., Fujii, T., and Ura, T. 1998. Neural network system for online controller adaptation and its application to underwater robot. In Proceedings of IEEE International Conference on Robotics & Automation, pp. 756–761.

C. Gaskett, D. Wettergreen, A. Zelinsky, Reinforcement Learning applied to the control of an Autonomous Underwater Vehicle, Australian

Conference on Robotics and Automation, Brisbane, Australia, pp. 125-131, March 1999

D.B.Marco, A.J.Healey, R.B.McGhee, Autonomous Underwater Vehicles: Hybrid Control of Mission and Motion, Autonomous Robots 3, 1996, pp.169-186

J.H. Li, B.H. Jun, P.M. Lee, S.W. Hong, A Hierarchical Real-Time Control Architecture for A Semi-Autonomous Underwater Vehicle, Journal of Ocean Engineering, 2005, Vol.32, pp.1631-1641

V. Sankaranarayanan, A.D. Mahindrakar, R.N. Banavar, A Switched Controller for an Underactuated Underwater Vehicle, Journal of Communications in Nonlinear Science and Numerical Simulation, 2007

M. Narasimhan, S.N. Singh, Adaptive Input-Output Feedback Linearizing Yaw Plane Control of BAUV using Dorsal Fins, Journal of Ocean Engineering, 2006, Vol.33, pp.1413-1430

M.S. Triantafyllou and M.A. Grosenbaugh, “Robust Control for Underwater Vehicle Systems with Time Delays,” IEEE Journal of Oceanic Engineering, vol.16, no.1, pp.146-151, 1991.

R.K. Lea, R. Allen, and S.L.Merry, A Comparative study of control techniques for an underwater flight vehicle. International Journal of System Science, 1999, volume 30, number 9, pages 947-964

Muljowidodo, S.D. Jenie, A. Budiyono and S. Adinugroho, Design, Development and Testing of Underwater Vehicles: ITB Experience. The

International Conference on Underwater System Technology: Theory and Application, Penang, Malaysia, 18-21 July 2006

Muljowidodo and A. Budiyono, Recent Progress in the Research on Unmanned Underwater Vehicles at ITB, Workshop on Underwater System Technology, Kuala Lumpur, Malaysia, December 11-12, 2007

A. Budiyono, A. Sugama and Muljowidodo, Dynamics Analysis of AUV Sotong, USYS08, Bali, November, 2008

J.M. Maciejowski, Predictive Control with Constraints, Pearson Education, 2002



  • There are currently no refbacks.