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| 基于PSO算法的系统辨识方法 | |
| 引用本文： | 徐小平,QIAN Fu-cai,刘丁,WANG Feng,王峰.基于PSO算法的系统辨识方法[J].系统仿真学报,2008,20(13). |
| 作者姓名： | 徐小平 QIAN Fu-cai 刘丁 WANG Feng 王峰 |
| 作者单位： | 1. 西安理工大学自动化与信息工程学院,陕西,西安,710048;西安理工大学理学院,陕西,西安,710048 2. 西安理工大学自动化与信息工程学院,陕西,西安,710048 3. 西安交通大学理学院,陕西,西安,710049 |
| 基金项目： | 高等学校博士学科点专项科研项目，陕西省自然科学基金 |
| 摘 要： | 研究了利用粒子群优化(particle swarm optimization, PSO)算法对系统进行辨识的新颖方法.该系统辨识方法的基本思想是将典型数学模型的相互组合而构成系统模型,即就是首先将系统结构辨识问题转化为组合优化问题,然后再采用粒子群优化算法同时实现系统的结构辨识与参数辨识.最后,给出了仿真示例,其仿真结果验证了所给的系统辨识新方法的合理性和有效性,辨识精度高,具有良好的实用性. |
| 关 键 词： | 结构辨识 参数辨识 粒子群优化 元模型 |
Method of System Identification Based on PSO Algorithm |
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| QIAN Fu-cai,WANG Feng.Method of System Identification Based on PSO Algorithm[J].Journal of System Simulation,2008,20(13). | |
| Authors: | QIAN Fu-cai WANG Feng |
| Abstract: | A novel method was studied for system identification based on particle swarm optimization(PSO) algorithm. The basic idea of the method employs a system model composed with classical models so as to transform the system structure identification problem into a combinational optimization problem. A PSO algorithm is then adopted to implement the identification on the system structure and parameters. Finally,simulation results show the rationality and effectiveness of the presented new method,and that the new method has high identification accuracy and very practical. |
| Keywords: | structure identification parameter identification particle swarm optimization(PSO) meta model |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |