Underwater robotic vehicles(URVs) have been an important tool for various underwater tasks such as pipe-lining, data collection, hydrography mapping, construction, maintenance and repairing of undersea equipment, etc because they have greater speed, endurance, depth capability, and safety than human divers. As the use of such vehicles increases, the vehicle control system is one of the most critical subsystems to increase autonomy of the vehicle. The vehicle dynamics are nonlinear and their hydrodynamic coefficients are often difficult to estimate accurately. It is desirable to have an intelligent vehicle control system because the fixed-parameter linear controller such as PID may not be able to handle these changes promptly and result in poor performance. In this paper we described and analyzed a new type of fuzzy model-based controller which is designed for underwater robotic vehicles and based on Takagi-Sugeno-Kang(TSK) fuzzy model. The proposed fuzzy controller: 1) is a nonlinear controller, but a linear state feedback controller in the consequent of each local fuzzy control rule; 2) can guarantee the stability of the closed-loop fuzzy system; 3) is relatively easy to implement. Its good performance as well as its robustness to parameter changes will be shown and compared with those of the PID controller by simulation.