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To have a complete model of a thunniform Fish-Robot, models of both body and tail are required. The dynamic model of the body is developed according to the parameters of a thunniform Fish-Robot built in MIT University, while, as the main part of this paper, the dynamic model of the tail is developed using fuzzy logic. Using experimental data and table look-up scheme, a fuzzy black box is introduced that gives the value of thrust force generated for any value of the Fish-Robot's input parameters: frequency of tail oscillation, amplitude of tail oscillation and speed of the Fish-Robot. In the second part, a trajectory fuzzy controller is designed for the Fish-Robot. The output of trajectory controller is force but the desired parameters to actuate the tail are frequency and amplitude. Therefore subtractive clustering method is used on the results of previous fuzzy black box to generate a fuzzy inference system. This system generates operational values of frequency and amplitude of oscillation for any force required. Control goals are achieved by putting the three units in a closed loop system.