Development of the AUV ‘ISiMI’ and a free running test in an Ocean Engineering Basin

Jun, Bong-Huan; Park, Jin-Yeong; Lee, Fill-Youb; Lee, Pan-Mook; Lee, Chong-Moo; Kim, Ki‐Hun; Lim, Yong‐Kon; Oh, Jun-Ho

doi:10.1016/j.oceaneng.2008.07.009

Cited by 95 publications

(34 citation statements)

References 13 publications

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“…9 and classifying the terms in the dynamic equation, we get the following equation for ISiMI: hydrodynamic coefficients in the model were estimated using the Nernstein and Smith method and the Prestero method. The developed coefficients were non-dimensionalized with the length of the vehicle and are listed in (Jun et al, 2008). The roll damping coefficient was analogized from that of similar vehicles.…”

Section: Numerical Model and Controller Design 41 Numerical Modelmentioning

confidence: 99%

“…The velocity v in (3) are the linear and angular velocity transformation matrices referred to in (Jun et al, 2008). Based on the non-linear dynamics of ISiMI, we developed a simulation environment for it using MatLab and Simulink.…”

Section: Numerical Model and Controller Design 41 Numerical Modelmentioning

confidence: 99%

“…The simplified equations for the steering and diving motions were derived by ignoring the cross-flow terms and higher-order terms. (Jun et al, 2008) The linearized steering system dynamics are given by: The sliding poles of the steering system arbitrarily at [0 -2], we got the steering control law as:…”

Section: Controller Design For Free Running Testsmentioning

confidence: 99%

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Development of Test-Bed AUV 'ISiMI' and Underwater Experiments on Free Running and Vision Guided Docking

Park¹,

Jun²,

Lee³

et al. 2009

Underwater Vehicles

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Section: Numerical Model and Controller Design 41 Numerical Modelmentioning

confidence: 99%

Section: Numerical Model and Controller Design 41 Numerical Modelmentioning

confidence: 99%

See 1 more Smart Citation

Development of Test-Bed AUV 'ISiMI' and Underwater Experiments on Free Running and Vision Guided Docking

Park¹,

Jun²,

Lee³

et al. 2009

Underwater Vehicles

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“…As an intercrossed subject of ocean engineering and robot technology, autonomous underwater vehicles (AUVs) have been widely employed in oceanic survey applications, including oceanographic mapping and detection, underwater resources exploration, undersea wreckage salvage, and so on [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Stability Control of Propeller Autonomous Underwater Vehicle Based on Combined Sections Method

Feng

Liu

et al. 2015

Polish Maritime Research

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Learning from the motion principle of quadrotor, a symmetric propeller AUV, which has small size and low velocity is designed. Compared with the AUV equipped with rudders, it has better maneuverability and manipulation at low velocity. According to the Newton-Euler method, the 6 DOF kinematic model and dynamic model of the propeller AUV are established. A stability controller that consists of 3 different PID controllers is designed. It makes the depth and attitude angle as trigger conditions, and the relevant controller is chosen in different moving

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“…Most existing gliders have used the PID and LQR controller to control the motion and attitude [1][2][3][4][5][6]. The sliding mode control (SMC) also has been used to control the underwater glider [7][8], but the main constraint in SMC is the chattering effect, which can degrade the performance of the system, and make the system unstable. Although these controller methods have already demonstrated acceptable results, the control system is considered as the Single-Input-Single Output (SISO) system.…”

Section: Introductionmentioning

confidence: 99%

An analysis of homeostatic motion control system for a hybrid-driven underwater glider

Isa

Arshad

2013

2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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Abstract-This paper presents an analysis of homeostatic controller, which controls the motion of a hybrid-driven underwater glider. The homeostatic controller is inspired from a biological process known as homeostasis, which maintains a stable state in the face of massively dynamics conditions. Within a biological context, organism homeostasis is an emergent property of the interactions between nervous, endocrine and immune system. Artificially these three systems are presented as Artificial Neural Network (ANN), Artificial Endocrine System (AES) and Artificial Immune System (AIS). The ANN is designed as the controller backbone, the AES is designed as the weight tuner, and the AIS is designed as the optimizer of the control system. The design objective is to obtain better control performance of the motion control system which includes the disturbance from the water currents. We have simulated the algorithm by using Matlab TM , and the results demonstrated that the homeostatic controller reduced the cost function of the control system and produced better control performance than the neuroendocrine controller.

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Development of the AUV ‘ISiMI’ and a free running test in an Ocean Engineering Basin

Cited by 95 publications

References 13 publications

Development of Test-Bed AUV 'ISiMI' and Underwater Experiments on Free Running and Vision Guided Docking

Development of Test-Bed AUV 'ISiMI' and Underwater Experiments on Free Running and Vision Guided Docking

Stability Control of Propeller Autonomous Underwater Vehicle Based on Combined Sections Method

An analysis of homeostatic motion control system for a hybrid-driven underwater glider

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