This paper presents a hybrid metaheuristic optimization algorithm that combines Particle Filter (PF) and Particle Swarm Optimization (PSO) algorithms. The new Particle Filter-Particle Swarm Optimization (PF-PSO) algorithm consists of two steps: the first generates randomly the particle population, and the second zooms the search domain. An application of this algorithm to the optimal tuning of Proportional-Integral-fuzzy controllers for the position control of a family of integral-type servo systems is then presented as a second contribution. The reduction of PF-PSO algorithms cost function allows for reduced energy consumption of the fuzzy control system. A comparison with other metaheuristic algorithms on canonical test functions and experimental results are presented at the end of the paper.