Nowadays, the control of Unmanned Aerial Vehicles (UAVs), achieving optimal stability and performance, is very important, particularly under complex conditions. Conventional Proportional, Integral, and Derivative (PID) controllers are widely used in UAVs. However, these type of controllers needs to adjust the parameters to work correctly in dynamic environments. This paper proposes an optimization approach that combines Particle Swarm Optimization (PSO) with fuzzy logic for parameter adaptation. The PSO optimization method is used to calculate the best PID gains, ensuring a good convergence in the PSO algorithm. A fuzzy logic system dynamically adjusts the important parameters of the PSO algorithm.