Control of an Unmmaned Underwater Vehicles Using an Optimized LQR Method

Ismaila B. Tijani, Agus Budiyono

Abstract


This paper presents an optimal control synthesis for an unmanned underwater vehicle using a Multiobjectives Differential Evolution (MODE)-based LQR approach. Although, the LQR control is a well-known optimal control method, the optimality of the resulting compensator is a subject of appropriate design parameters’ (Q and R) selection. Considering the complex dynamics nature of an unmanned underwater vehicle, and the need to achieve optimal compromise between several control performance objectives such as time response, control energy minimization and robustness, the conventional LQR design approach is not only potentially challenging, it is time consuming and  limits the achievable performance. In this paper, the control problem is formulated as a Multiobjectives optimization problem to search for Pareto-based optimal (sub-optimal) design parameters using a MODE-algorithm.  The performance evaluation of the resulting compensator in simulation shows an effective compromise between the conflicting performance objectives, while the design approach is observed to be effective in rapid prototyping and deployment of such vehicle.

Keywords


LQR, optimal control, Multiobjectives,Differential Evolution, optimization.

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References


Ura T., AUV ‘r2D4’, Its Operation, and Road Map for AUV Development, in: Advances in Unmanned Marine Vehicles, edited by G.N. Roberts & R. Sutton, ( IEE Control Series 69) 2006.

A. Budiyono, Muljowidodo and A. Sugama, “Coefficient Diagram Method for the Control of an Unmanned Underwater Vehicle,” Indian J Mar Sci., 38(3):316-323, Sept. 2009

R. K. Lea, R. Allen and S. L.Merry, “A comparative study of control techniques for an underwater flight vehicle,” International Journal of Systems Science, volume 30, number 9, 1999, pp. 947- 964. CrossRef

Agus Budiyono, “Advances in unmanned underwater vehicles technologies: Modeling, control and guidance perspectives’, Indian J. of Geo-Marine Sciences, October 2009.

Herman, P., Decoupled PD set-point controller for underwater vehicles. Ocean Engineering, 2009, vol. 36, no. 6-7, p. 529 to 534.

Wei YH, Peng FG, Sheng C, et al. Control method of the stability of AUV. J Huazhong Univ Sci Technol Nat Sci Ed 2014; 42: 127–132.

Rodrigues, L., Tavares, P., Prado, M. Sliding mode control of an AUV in the diving and steering planes. In Proceedings of the MTS/IEEE Oceans’06 Conference. FortLauderdale (FL, USA), 1996, p. 576 - 583. CrossRef

Sabiha A Wadoo, Sadiksha Sapkota, Keerthish Chagachagere, “Optimal Control of an Autonomous Underwater Vehicle’, Systems, applications and technology conference (LISAT), 4 May, 2012, IEEE Long Island.

Field, A. I., Cherches, D., Calisal, S. Optimal control of an autonomous underwater vehicle. In Proceedings of the World Automatic Congress. Hawaii (USA), 2000, vol. 1, no. 38.

Lin-LinWang,Hong-JianWang, and Li-Xin Pan. ‘H∞ control for path tracking of autonomous underwater vehicle motion, Advances in Mechanical Engineering 2015, Vol. 7(5) 1–18.

Triantafyllou M.S. & Grosenbaugh M.A., Robust Control for Underwater Vehicle Systems with Time Delays, IEEE Journal of Oceanic Engineering, 16(1991) 146-151. CrossRef

Yuh J., A Neural Net Controller For Underwater Robotic Vehicles, IEEE Journal of Oceanic Engineering, 15 (1990), 161-166. CrossRef

Craven, P. J. (1999). Intelligent control strategies for an autonomous underwater vehicle. PhD Thesis,University of Plymouth, UK. CrossRef

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

M. Castillo-Effen, C. Castillo, W. Moreno, K. P. Valavanis, (2007). “Control Fundamentals of Small /Miniature Helicopters - A Survey”. Kimon P. Valavanis (ed.), Advances in Unmanned Aerial Vehicles, 73-118. © 2007 Springer. Printed in the Netherlands. CrossRef

W. Alvis, C. Castillo, M. Castillo-Effen, W. Moreno, K. P. Valavanis, (2007) “A Tutorial Approach to Small Unmanned Helicopter Controller Design for Nonaggressive Flights” Kimon P. Valavanis (ed.), Advances in Unmanned Aerial Vehicles, 119–170. © 2007 Springer. Printed in the Netherlands.

Brian L. Stevens and Frank L. Lewis, (1992). Aircraft control and simulation, John Wiley & Sons, Inc.

Ismaila B. Tijani, Rini Akmeliawati, Ari Legowo and A. G. Abdul Muthalif, 2011. Optimized LQR Control For 3DOF Helicopter Using Multiobjective Differential Evolution (Mode), in Computational Intelligent in Robust Control, IIUM Press.

Tijani I.B.. Flight control system with MODE based H-infinity for small scale autonomous helicopter. PhD thesis submitted to Mechatronics engineering department, IIUM,Malaysia, October 2012.

Ismaila B. Tijani, Rini Akmeliawati, Ari Legowo and Agus Budiyono, (2015). “Optimization of H-infinity Controller for Unmanned helicopter control using Pareto-based Multiobjective Differential Evolution.” Journal of Aerospace Engineering and Aircraft Technology, (AEAT).

Muljowidodo, Jenie S.D., Budiyono A. & Adinugroho S., Design, Development and Testing of Underwater Vehicles: ITB Experience, paper presented at The International Conference on Underwater System Technology: Theory and Application, Penang, Malaysia, 2006.

Storn, R. and Price, K.. Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces, Journal of Global Optimization 11: 341–359, 1997, 341 1997 Kluwer Academic Publishers, 1997.

Bourhane Kadmiry, (2002), ‘Fuzzy Control for an Unmanned Helicopter’, PhD thesis, Linköping Studies in Science and Technology, Department of Computer and Information Science, Linköpings Universitet, SE-581, 83 Linköping, Sweden




DOI: http://dx.doi.org/10.21535%2Fmust.v1i2.897

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