Abstract: Particle swarm optimization algorithm is a typical swarm intelligence algorithm,the diversity of the population is an important factor to affect the optimize performance of particle swarm optimization algorithm.Several methods that control the population diversity are analyzed,such as the initial position of the particle,the mutation of particle that perform during the iterative process,asynchronous update strategy,and asynchronous update strategy with a linearly decreasing inertia weight.Some test functions are used for simulation experiments,and several control methods of the diversity that can improve the performance of particle swarm optimization are given.