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Ensemble Kalman Filter with a Square Root Scheme (EnKF-SR) for Trajectory Estimation of AUV SEGOROGENI ITS

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Results of a study on the development of navigation system and guidance for AUV are presented in this paper. The study was carried to evaluate the behavior of AUV SEGOROGENI ITS, designed with a characteristic length of 980 mm, cross-section diameter of 180 mm, for operation in a 3.0 m water depth, at a maximum forward speed of 1.94 knots. The most common problem in the development of AUVs is the limitation in the mathematical model and the restriction on the degree of freedom in simulation. In this study a model of linear system was implemented, derived from a non-linear system that is linearized utilizing the Jacobian matrix. The linear system is then implemented as a platform to estimate the trajectory. In this respect the estimation is carried out by adopting the method of Ensemble Kalman Filter Square Root (EnKF-SR). The EnKF-SR method basically is developed from EnKF at the stage of correction algorithm. The implementation of EnKF-SR on the linear model comprises of three simulations, each of which generates 100, 200 and 300 ensembles. The best simulation exhibited the error between the real tracking and the simulation in translation mode was in the order of 0.009 m/s, whereas in the rotation mode was some 0.001 rad/s. These fact indicates the accuracy of higher than 95% has been achieved.
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AUV; EnKF-SR; Linear System; Trajectory Estimation

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Herlambang, T., Nurhadi H and Subchan., 2014a “Preliminary Numerical Study on Designing Navigation and Stability Control Systems for ITS AUV”, Applied Mechanics and Materials Vol. 493 (2014) pp 420-425 Trans Tech Publications, Switzerland.

Yang, C. 2007. Modular Modelling and Control for Autonomous Vehicle (AUV). Department of Mechanical Engineering National University of Singapore

Pascoal, A. (1994).The AUV MARIUS: Mission Scenarios, Vehicle Design, Construction and Testing. Proceedings of the 2nd Workshop on Mobile Robots for Subsea Environments. Monterey Bay Aquarium, Monterey, California, USA.

Lewis, L Frank. (1986), “Optimal Estimation, With An Introduction To Stochastic Control Theory”, John Wiley and Sons, New York.

Evensen, G (2009), “Data Asimilation The Ensemble Kalman Filter (second edition)”, Springer-Verlag Berlin Hiedelberg London and New York

Herlambang, T. (2012), “Square Root Ensemble Kalman Filter (SR-EnKF) for Estimation of Missile Position”, Magister Thesis, Department of Mathematics Sepuluh Nopember Institut of Technology, Surabaya.

Fosen, T. I.2005. A Nonlinear Unified State-space Model for Ship Maneuvering and Control in A Seaway-Journal of Bifurcation and Chaos, Int. J. Bifurcation Chaos, 15, 2717 (2005)..

Perez, T. O. N. Smogeli, T.I Fossen and A.J Sorensen. 2005. An Overview of marine Systems Simulator (MSS): A Simulink Toolbox for Narine Control System . SIMS2005-Scandanavian Conference on Simulation and Modelling.

SNAME, The Society of Naval Architects and Marine Engineers, “Nomenclature for Treating the Motion of A Submerged Body Through A Fluid”, Technical and Research Bulletin, no. 1-5, 1950.

Subiono. 2010. “Mathematical system”. Department of Mathematics Sepuluh Nopember Institut of Technology, Surabaya.

Herlambang, T., Djatmiko E.B and Nurhadi H., 2014b. “Optimization with Jacobian Approach for ITS AUV System”, international conference on Marine Technology.

Bennassar, A., Abbou, A., Akherraz, M., Barara, M., A new sensorless control design of induction motor based on backstepping sliding mode approach, (2014) International Review on Modelling and Simulations (IREMOS), 7 (1), pp. 35-42.

Angrisani, L., Liccardo, A., Pasquino, N., Lo Moriello, R.S., Bifulco, P., Laracca, M., Lanzolla, A.M., On the suitability of DEKF for improving GPS location in car accidents, (2013) International Review on Modelling and Simulations (IREMOS), 6 (5), pp. 1600-1606.

Ferdowsi, M.H., Passive range estimation using two and three optical cameras, (2013) International Review on Modelling and Simulations (IREMOS), 6 (2), pp. 613-618.

Moujahed, M., Ben Azza, H., Jemli, M., Boussak, M., Speed estimation by using EKF techniques for sensor-less DTC of PMSM with Load Torque Observer, (2014) International Review of Electrical Engineering (IREE), 9 (2), pp. 270-279.


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