粒子群优化
PID控制器
控制理论(社会学)
计算机科学
控制器(灌溉)
算法
多群优化
控制工程
工程类
控制(管理)
人工智能
温度控制
农学
生物
作者
Yanzi Miao,Yang Liu,Ying Chen,Huijie Jin
标识
DOI:10.2991/iceem-15.2015.26
摘要
Improved PSO algorithms combined with Simulated Annealing are proposed in this paper to solve the problems of the original PSO algorithm.After that three further improvements are proposed respectively from the parameters adjustment, the organization structure and evolution, and the topology structure.Four common test functions are used to test the optimizing performances of the improved PSO algorithms in the paper.The test results indicate that all the improved PSO algorithms have better performances compared with former PSO algorithms.Finally, the improved PSO algorithm is applied to PID parameter tuning, and the simulation experiment results prove that the improved PSO algorithm proposed in this paper is more feasible than other intelligent algorithms.
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