Researching and Development of an Autonomous Underwater Vehicles with Capability of Collecting Solar Energy
Main Article Content
Abstract
Autonomous Underwater Vehicles (AUV) is an unmanned underwater device with capability of performing a variety of missions in the water environment such as ocean operation, offshore waters, polluted water investigation including: marine scientific research, maritime monitoring, exploration, marine economics, oil and gas, security and defense, surveillance and measurement and in rescue and salve. In this article, the authors developed a model of AUV with retractable wings and evaluate the efficiency of solar energy collection. The establishment of the controller to adapt the stability requirements, in accordance with the model of equipment S-AUV (Solar - Autonomous Underwater Vehicles) was built. The hydrodynamic equations with the predefined conditions were modeled and solved. The Hierarchical Sliding Mode Controller (HSMC) for the S-AUV were applied in this research. Experimental results showed that the efficiency of the collection of the solar cell has been significantly improved comparing to a diving equipment without retractable energy wings. In addition, the simulation results showed that the developed controller performed much better control quality, adhering to the set value with the error within the permissible limit.
Keywords
Autonomous underwater vehicles, energy solar, underactuated system, control AUV, hierarchical sliding mode controller
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
[1]. U.S. Commission on Ocean Policy, An ocean blueprint for the 21st century, final report, Washington D.C., 2004, ISBN# 0-9759462-0-X.
[2]. Denise M. Crimmins, Christopher T. Patty. Long Endurance Test Results of the Solar-Powered AUV System, 2006, 1-4244-01 15-1/06. IEEE.
[3]. http://nangluongvietnam.vn/news/vn/dien-hat-nhan-nang-luong-tai-tao/cap-nhat-so-lieu-khao-sat-cuong-do-buc-xa-mat-troi-o-viet-nam.html.
[4]. Nguyen Van Tuan, Dinh Van Phong, Nguyen Chi Hung and Hoang The Phuong. Studying the effects of the energy wing on the motion resistance of the AUV when integrating the solar collection system. The 10th National Mechanical Conference, December 2017. ISBN 978-604-913-719-8. pp309-318.
[5]. T. I. Fossen, O.-E. Fjellstad (1995) Nonlinear modelling of marine vehicles in 6 degrees of freedom. Mathematical Modelling of Systems, 1995, vol. 1 no. 1, pp. 17–27 https://doi.org/10.1080/13873959508837004
[6]. Wadoo S, Kachroo , Autonomous underwater vehicles: modeling, control design and simulation. CRC Press, February 2011. ISBN 978-1439818312.
[7]. Cooney LA, Dynamic response and maneuvering strategies of a hybrid autonomous underwater vehicle in hovering. Thesis of Master of Science in ocean engineering, Massachusetts Institute of Technology, 2009.
[8]. Buckham BJ, Podhorodeski RP, Soylu S , A chattering-free sliding-mode controller for underwater vehicles with fault tolerant infinity-norm thrust allocation. J Ocean Eng, 2008, 35(16):1647–1659. https://doi.org/10.1016/j.oceaneng.2008.07.013
[9]. Qi X, Adaptive coordinated tracking control of multiple autonomous underwater vehicles. Ocean Eng, 2014, 91:84–90. https://doi.org/10.1016/j.oceaneng.2014.08.019
[10]. Jun SW, Kim DW, Lee HJ, Design of T-S fuzzy model based controller for depth control of autonomous underwater vehicles with parametric uncertainties. In: 2011 11th international conference on control, automation and systems, ICCAS 2011, Gyeonggi-do, Republic of Korea, 2011, pp 1682–1684.
[11]. Medagoda L, Williams SB, Model predictive control of an autonomous underwater vehicle in an in situ estimated water current profile. Oceans, 2012, Yeosu, pp 1–8. https://doi.org/10.1109/OCEANS-yeosu.2012.6263604
[12]. Xu B, Pandian SR, Sakagami N, Petry F, Neurofuzzy control of underwater vehicle-manipulator systems. J Franklin Institute, 2012, 349(3):1125–1138. https://doi.org/10.1016/j.jfranklin.2012.01.003
[2]. Denise M. Crimmins, Christopher T. Patty. Long Endurance Test Results of the Solar-Powered AUV System, 2006, 1-4244-01 15-1/06. IEEE.
[3]. http://nangluongvietnam.vn/news/vn/dien-hat-nhan-nang-luong-tai-tao/cap-nhat-so-lieu-khao-sat-cuong-do-buc-xa-mat-troi-o-viet-nam.html.
[4]. Nguyen Van Tuan, Dinh Van Phong, Nguyen Chi Hung and Hoang The Phuong. Studying the effects of the energy wing on the motion resistance of the AUV when integrating the solar collection system. The 10th National Mechanical Conference, December 2017. ISBN 978-604-913-719-8. pp309-318.
[5]. T. I. Fossen, O.-E. Fjellstad (1995) Nonlinear modelling of marine vehicles in 6 degrees of freedom. Mathematical Modelling of Systems, 1995, vol. 1 no. 1, pp. 17–27 https://doi.org/10.1080/13873959508837004
[6]. Wadoo S, Kachroo , Autonomous underwater vehicles: modeling, control design and simulation. CRC Press, February 2011. ISBN 978-1439818312.
[7]. Cooney LA, Dynamic response and maneuvering strategies of a hybrid autonomous underwater vehicle in hovering. Thesis of Master of Science in ocean engineering, Massachusetts Institute of Technology, 2009.
[8]. Buckham BJ, Podhorodeski RP, Soylu S , A chattering-free sliding-mode controller for underwater vehicles with fault tolerant infinity-norm thrust allocation. J Ocean Eng, 2008, 35(16):1647–1659. https://doi.org/10.1016/j.oceaneng.2008.07.013
[9]. Qi X, Adaptive coordinated tracking control of multiple autonomous underwater vehicles. Ocean Eng, 2014, 91:84–90. https://doi.org/10.1016/j.oceaneng.2014.08.019
[10]. Jun SW, Kim DW, Lee HJ, Design of T-S fuzzy model based controller for depth control of autonomous underwater vehicles with parametric uncertainties. In: 2011 11th international conference on control, automation and systems, ICCAS 2011, Gyeonggi-do, Republic of Korea, 2011, pp 1682–1684.
[11]. Medagoda L, Williams SB, Model predictive control of an autonomous underwater vehicle in an in situ estimated water current profile. Oceans, 2012, Yeosu, pp 1–8. https://doi.org/10.1109/OCEANS-yeosu.2012.6263604
[12]. Xu B, Pandian SR, Sakagami N, Petry F, Neurofuzzy control of underwater vehicle-manipulator systems. J Franklin Institute, 2012, 349(3):1125–1138. https://doi.org/10.1016/j.jfranklin.2012.01.003