Particle swarm optimization (PSO) has been shown to be an efficient, robust and simple optimization algorithm. Aim at the shortcoming that the PSO algorithm falls into local optimization easily, in this paper fuzzy control theory is introduced into PSO (FPSO). Parameters may be dynamic adjusted themselves according to the optimization effect every time in this algorithm. Its ability of dynamic adjustment is strengthened, and the global optimization performance of the algorithm can be improved better. And in this paper, the improved algorithm is illustrated how could solve the problem, which exists in the raw material requirement model for production processing in the ore dressing plant. The experimental results are provided to support the conclusions drawn from the theoretical findings.