This paper presents a design of self-tuning gain depth controller for the autonomous underwater vehicle KAUV-1 which has been under development at the Intelligent Robot & Automation Lab, Korea Maritime University (KIAL). The vehicle is shaped like a torpedo with light weight and small size and used for marine exploration and monitoring. The KAUV-1 has a unique ducted propeller located at aft end with yawing actuation acting as a rudder. For depth control, the KAUV-1 uses a mass shifter mechanism to change its center of gravity, consequently, can control pitch angle and depth of the vehicle. A design of classical PD depth controller for the KAUV-1 was presented and analyzed in [11]. However, it has inherent drawback of gains, that is their values are fixed. Meanwhile, in different operation modes, vehicle dynamics might have different impacts on the behavior of the vehicle, for example, ones in modes of diving and moving up as mentioned in [11]. This requires a set of flexible or self-tuning gains, i.e., their values are appropriately changed according to vehicle operating states, for a better performance. This paper presents a self-tuning gain depth controller using fuzzy logic method which based on the classical PD controller derived from [11]. Its self-tuning gains are outputs of fuzzy logic blocks. Fuzzy logic is a simple and efficient control method very suitable for this case because it could be designed based on designer's sense and experience with flexible rules without a model. The performance of the self-tuning gain controller will be simulated by Matlab/Simulink and compared to the one of the classical PD controller.