Abstract
In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.
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Mohammad Pourmahmood Aghababa received his B.S. degree in Biomedical Engineering from Isfahan University in 2005. He received his M.S. and Ph.D. degrees both in Control Engineering from the University of Tabriz in 2007 and 2011, respectively. He is currently an Assistant Professor in the Department of Electrical Engineering of the Urmia University of Technology, Urmia, Iran. His research interests include nonlinear control, fractional calculus, and artificial intelligence.
Mohammad Hossein Amrollahi received his B.S. and M.S. degrees both in Electrical Engineering from Sharif University of Technology and the University of Tehran in 1990 and 1994, respectively. He is now a lecturer in the Department of Electrical Engineering of the Urmia University of Technology, Urmia, Iran. His research interests include power systems, renewable energy, and artificial intelligence.
Mehdi Borjkhani received his B.S. degree in Electrical Engineering from Urmia University in 2005. He got his M.S. in Biomedical Engineering from Amirkabir University in 2009. He is now a lecturer in the Department of Electrical Engineering of the Urmia University of Technology, Urmia, Iran. His research interests include signal processing, handwriting techniques, and artificial intelligence.
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Aghababa, M.P., Amrollahi, M.H. & Borjkhani, M. Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles. J. Marine. Sci. Appl. 11, 378–386 (2012). https://doi.org/10.1007/s11804-012-1146-x
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DOI: https://doi.org/10.1007/s11804-012-1146-x