Quantum Particle Swarm Evolutionary Algorithm with Application to System Identification

摘要：

Based on quantum evolutionary algorithm and particle swarm optimization, a quantum particle swarm evolutionary algorithm is proposed. In this algorithm, quantum angle is used to represent the qubit, a new method learning from the idea of particle swarm algorithm is presented to determine rotation angle, He gate is taken to prevent from premature convergence. Applying this algorithm to identify system parameter, and comparing with conventional genetic algorithm and quantum evolutionary algorithm, the experimental results illustrate that the proposed algorithm has better performance than that of others. Meanwhile, it can also keep high identification ability to the system with the existence of noise.

关键词： quantum particle swarm evolutionary algorithm rotation angle Hεgate parameter identification noise

作者: LI Hao LI Shiyong

作者单位: Department of Control Science and Engineering Harbin Institute of Technology Harbin, China

会议类型: 国际会议

会议名称: 2012 International Conference on Measurement,Information and Control(2012测量、信息与控制国际会议 ICMIC2012)

会议地点: 哈尔滨

会议语种:英文

页码: 1019-1023

在线出版日期: 2012-05-18（万方平台首次上网日期，不代表论文的发表时间）