Adaptive depth controller design for a submerged body moving near free surface. (June 2016)

• Record Type: Journal Article
• Authors: Park, Jong-Yong; Kim, Nakwan; Yoon, Hyeon Kyu; Cho, Hyeonjin
• Is Part Of: Applied ocean research. Volume 58(2016:Oct.)
• Page Start: 83
• Page End: 94
• Publication Date: 2016-06
• Subjects: Submerged body -- Depth control -- Adaptive control -- Environmental load -- Free surface effect; Ocean engineering -- Periodicals; 620.416205
• DOI: 10.1016/j.apor.2016.04.001
• Languages: English
• ISSNs: 0141-1187

Abstract

Highlights: This paper has presented our study on modeling of the wave excitation, suction, and current forces for a controller designed for a submerged body that moves near a free surface. The wave exciting force acting on the submerged body is derived, and an irregular wave force is applied to the simulations based on the linear theory. The suction force is calculated using a double Rankine body under three speed and various depth conditions. The controller is constructed as a double loop to consider the characteristic of the submerged body. Simulations are conducted under various speed, depth, wave, and current conditions to verify the designed controller performance. The results of the depth control simulations performed to verify the derived control law confirm the effectiveness of the designed controller. Abstract: A submerged body that moves near a free surface needs to keep its attitude and position to accomplish its missions, which are required to validate the performance of a designed controller before sea trial. Hydrodynamic maneuvering coefficients are generally obtained by experiments or computational fluid dynamics, but these coefficients suffer from uncertainty. Environmental loads such as wave excitation, current, and suction forces act on the submerged body when it moves near the free surface. Therefore, a controller for the submerged body should be robust to parameter uncertainty and environmental loads. In this paper, six-degree-of-freedom equations of motion for the submerged body are constructed. An adaptive control method based on the neural network and proportional–integral–derivative controller is used for the depth controller. Simulations are performed under various depth and environmental conditions, and the results show the effectiveness of the designed controller.