Navigation and system identification of an unmanned underwater survey vehicle

Kartal, Seda Karadeniz
This study includes the mathematical model of an unmanned underwater vehicle, autopilot and the guidance design, the navigation solution and system identification of the unmanned underwater survey vehicle SAGA (Su Altı Gözlem Aracı). First, the 6 degrees-of-freedom (DOF) nonlinear mathematical model of an unmanned underwater vehicle is obtained by a Newton-Euler formulation. Then, the autopilot is designed by utilizing the proportional–integral–derivative (PID) control approach. The navigation problem is solved by integrating the inertial navigation system, acoustic and vision based measurement system and aiding sensors. All measurements are obtained in simulation environment. Performance of the resultant navigation system is analyzed by creating suitable system state, measurement and noise models. The navigational data of the vehicle is improved by utilizing a Kalman filter. After the navigation problem solved, guidance is performed by the way point guidance algorithm by line-of-sight (LOS) and the way point guidance based optimal control with navigational data. The pool experimental set-up is designed by using the inertial navigation system and acoustic-based measurement system composed of pinger and hydrophones together. These are integrated to obtain navigation data of the vehicle more accurately. In addition, the depth sensor is used in order to support depth information. The mathematical model of the vehicle includes some unknown parameters such as added mass and damping coefficients. It is not possible to determine all the parameters values as their effect on the state of the system is usually negligible. On the other hand, most of the “important” parameters are obtained based on a system identification study of the vehicle by using this estimated experimental navigational data for coupled motion. All of this study is performed in a Matlab/Simulink environment. 
Citation Formats
S. K. Kartal, “Navigation and system identification of an unmanned underwater survey vehicle,” Ph.D. - Doctoral Program, 2017.