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Due to the nonlinear and the time-varying parameters of the UAV model, controller design of traditional PID method of the dynamic and static performance may become very bad, in order to solve this problem, designing the fuzzy adaptive attitude controller for a certain type of UAV. To avoid the blindness of membership function in fuzzy controller selection problem, this paper uses the particle swarm optimization algorithm of intelligent optimization of membership function, reducing the influence of experts in the design process of the subjective intention of controller performance uncertainty. The simulation results show that the static and dynamic performance of the controller designed in this paper compared with the traditional PID is better, and has certain robustness to model time-varying parameters.