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Abstract

The underwater glider (UG) is an underwater exploration equipment that propels itself with very low power consumption by converting the vertical motion into a horizontal motion using a buoyancy control device and a wing. To enhance gliding performance of the UG, a hybrid underwater glider (HUG) has been developed to compensate for the disadvantages of slow speed and horizontal movement and limited navigation accuracy of the UG by attaching propellant to the UG [15].

In this paper, the structure, control system and control algorithm of the HUG are presented. Also, for the developed HUG, motion performance of the HUG is simulated by computer. To realize precise navigation of the developed HUG, an attitude reference system (ARS) composed of a ring laser gyroscope(RLG) and a geomagnetic sensor is developed with the Extended Kalman Filter (EKF) algorithm.

To control the HUG, the six degrees of freedom equations of the HUG with the hydrodynamic force coefficient were studied. A control algorithm based on the neural network was proposed to reduce tracking error of the HUG. To validate the proposed control algorithm, a computer simulation using Matlab / Simulink was performed [13].

Keywords

Hybrid underwater glider ARS (Attitude Reference System)underwater navigation neural network self- tuning -PID neural network - PID parallel controller

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Design and control of navigation system for hybrid underwater glider

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