Autonomous underwater vehicles could perform various underwater task, ranging from sea floor surveying, ocean cable iection and maintenance to petroleum drilling, lost asset location and underwater rescue. Some of these applications necessitate a very strict positioning and force requirement on to the AUV controller. However, the AUV dynamics is inherently nonlinear. It is also subject to uncertain external disturbances, and the hydrodynamic forces are difficult to model. All of these make AUV control a very challenging task. These vehicles require autonomous guidance and control systems in order to perform underwater tasks. Modeling, system identification and control of these vehicles are still major active areas of research and development. The control issue of underwater robots is very challenging due to the nonlinearity, time variance, unpredictable external disturbances, such as the sea current fluctuation, and the difficulty in accurately modeling the hydrodynamic effect. Conventional linear controllers may fail in satisfying performance requirements, especially when changes in the system and environment occur during the operation since it is almost impossible to manually retune the control parameters in water. Therefore, it is highly desirable to have an underwater robot controller capable of self-adjusting control parameters when the overall performance degrades. This thesis presents adaptive plus disturbance observer controller for underwater robots, which is robust with respect to external disturbance and uncertainties in the system. This control scheme consists of disturbance observer as the inner-loop controller and a nonregressor based adaptive controller as the outer-loop controller. This thesis describes an adaptive plus disturbance observer controller for underwater robots. The non regressor based adaptive controller does not require any physical information about the robot model except the number of inputs and the number of outputs. The non regressor based adaptive controller is very effective for autonomous underwater vehicles whose hydrodynamics can not be accurately modeled or may vary while in operation as some changes occur in the system and environment. Although, the adaptive controller does not address robustness with respect to external disturbances while disturbance observer is very robust with respect to external disturbances. The disturbance observer basically removes the effect of external disturbances and modeling errors, and makes the system behave close to a nominal model that was prechosen by the user. However, the disturbance observer controllers require using a low-pass filter affected by the nominal model, and therefore, the performance of the disturbance observer controller such as adaptive plus disturbance observer varies depending on the nominal model or the low-pass filter. In fact, in this thesis presents an adaptive disturbance observer controller using disturbance observer as an inner-loop compensator, taking advantage of its robustness with respect to disturbances, and using the non regressor based adaptive controller as an outer-loop controller, taking advantage of its robustness with respect to model uncertainties due to the nominal model or the low-pass filter. The effectiveness of the adaptive disturbance observer was investigated by simulating two control systems: adaptive controller and adaptive disturbance observer on an autonomous underwater robot, ODIN. The thesis is organized as follows. Section II and Section III describes the factors affecting an underwater vehicle and Section IV describes the adaptive disturbance observer controller and Section V presents simulation results before conclusions in Section VI. Keywords: Adaptive cont rol, disturbance observer, external disturbance, underwater robots.