海军航空大学学报2018，Vol.33Issue(2)：248-252,5.DOI:10.7682/j.issn.1673-1522.2018.02.012
基于模拟退火的改进粒子群算法研究及应用
Research and Application of Improved PSO Algorithm Based on Simulated Annealing
摘要
Abstract
In this paper, a new particle swarm optimization hybrid algorithm with constriction factors based on simulated annealing was presented in order to speed up the efficiency of PSO algorithm and jump out of the local optimal trap and gain the best solutions. Firstly, the hybrid optimization algorithm was analyzed, then the numerical simulation of hybrid op-timization algorithm was carried out. Lastly, SACPSO algorithm was applied to the PID parameter tuning problem. The ex-perimental results showed that the accuracy, stability and convergence speed of SACPSO algorithm had improved obvious-ly. Compared with traditional methods, SACPSO algorithm had better stability and convergence in PID parameter tuning problem.关键词
粒子群/模拟退火/收缩因子/SACPSO/参数整定Key words
particle swarm optimization/simulated annealing/constriction factors/SACPSO/parameter tuning分类
信息技术与安全科学引用本文复制引用
薛永生,吴立尧..基于模拟退火的改进粒子群算法研究及应用[J].海军航空大学学报,2018,33(2):248-252,5.基金项目
国家自然科学基金资助项目(51375490) （51375490）
