An Improved Quantum Particle Swarm Optimization and Its Application in System Identification

摘要：

　　In order to improve convergence speed and precision of optimization in quantum particle swarm optimization(QPSO),an improved quantum particle swarm optimization(IQPSO)algorithm was presented.Chaotic sequences were used to initialize the origin angle position of particle,mutation operation algorithm was used to increase diversity of population and avoid premature convergence.The proposed algorithm was applied to identify the classic adaptive infinite impulse response(IIR)model,the results show the validity of IQPSO.

关键词： Quantum particle swarm optimization System identification Adaptive IIR filter

作者: Huang yu Xiao tiantian Han pu

作者单位: Department of Automation,North China Electric Power University,Baoding China 071003

会议类型: 国际会议

会议名称: 第26届中国控制与决策会议(2014 CCDC)

会议地点: 长沙

会议语种:英文

页码: 1132-1134

在线出版日期: 2014-05-31（万方平台首次上网日期，不代表论文的发表时间）