粒子群优化算法的理论分析和避免早熟一直是被重点研究的两个问题,但前者因复杂的动态性而不得不在简化的系统条件下进行,后者因不可避免地引入形式多样的操作算子而增加了算法复杂性,进而使得理论分析更加困难.对此,本文整理归纳出了大多数现有改进算法的位置更新方程之间的共性规律,给出了统一形式,并由多阶随机差分方程简化为一阶随机差分方程,使得粒子搜索行为控制和收敛性分析更为容易.实验在具有代表性的算法上进行,验证了对位置更新方程的统一和简化过程的合理性,并表明本文方法性能更具有竞争力. Particle Swarm Optimization (PSO) theory analysis and avoidance of precocity are two major issues that have been focused on. However, the former has to be implemented in a simplified system due to its complex dynamics. The latter, due to the inevitable introduction of various operators Which increases the complexity of the algorithm and makes the theoretical analysis even more difficult.In this paper, we generalize the common law between the location updating equations of most existing improved algorithms, give a uniform form, The equation is simplified as a first-order stochastic difference equation, which makes particle search behavior control and convergence analysis easier.Experiments are carried out on a representative algorithm to verify the unity of the location update equation and the rationality of the simplification process, Method performance is more competitive.