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B. Ferreira, M. Pinto, A. Matos, and N. Cruz, "Hydrodynamic modeling and motion limits of auv mares," in 35th Annual Conference of IEEE on Industrial Electronics, Proto, 2241-2246.

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Modeling and Control Approach for a Complex-Shaped Underwater Vehicle

1Department of Mechanical Engineering, University of Peradeniya, KY 20400, Sri Lanka

American Journal of Mechanical Engineering. 2019, Vol. 7 No. 4, 158-171
DOI: 10.12691/ajme-7-4-2
Copyright © 2019 Science and Education Publishing

Cite this paper:
G.A.C.T. Bandara, D.A.A.C. Ratnaweera, D.H.S. Maithripala. Modeling and Control Approach for a Complex-Shaped Underwater Vehicle. American Journal of Mechanical Engineering. 2019; 7(4):158-171. doi: 10.12691/ajme-7-4-2.

Correspondence to: G.A.C.T.  Bandara, Department of Mechanical Engineering, University of Peradeniya, KY 20400, Sri Lanka. Email:


This paper presents the trajectory tracking and the path planning algorithm based on an adaptive control law to operate a complex-shaped low speed autonomous underwater vehicle (AUV) in a challenging environment of non-linearity, time variance and unpredictable external disturbances. Firstly, computational fluid dynamic (CFD) simulations are used to compute the added mass matrix and the damping matrix. Secondly, the adaptive controller is implemented to track the desired trajectory. This desired state-dependent regressor matrix-based controller provides consistent results even under hydrodynamic parametric uncertainties. The stability of the developed controller is verified using Lyapunov’s direct approach. Moreover, the proposed control law adopts quaternions to represent the attitude errors and thus avoids the representation of singularities that occur when using the Euler angle description of the orientation. Thirdly, an efficient underwater path planning algorithm is developed based on vehicle-fixed-frame error variables. The simulations are done to compute the optimal path of the AUV which minimizes the travelling time. Finally, an optimal thrust allocation for the desired values of forces and moments acting on the vehicle is found via a model-based unconstrained thrust allocation. The results show that the AUV asymptotically converges on the desired trajectory and the path with a minimum time. At this moment, the propulsion forces approach zero, which further assures the accuracy of the controller. Hence, the effectiveness and the robustness of the developed algorithm are acceptable to design the AUV.