| 摘要: |
| 研究了一种线性系统的参数精确辨识方法；首先采用PSO（Particle Swarm Optimization，粒子群优化）方法对模型进行优化迭代，并选择合适误差准则作为粒子群优化算法的适应度函数，以迭代每个粒子所对应的参数速度和大小；在此基础上，寻找最小适应度值的粒子，推导出最优的适应度函数值，实现系统参数的实时、精确估计；最后通过实验验证了基于粒子群优化算法的参数辨识法的准确性和有效性。 |
| 关键词: 参数辨识 PSO方法 准则函数 |
| DOI： |
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| Research on Parameter Identification Method for a Class of Linear System Based on PSO |
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LI Zhen1, WEI Li sheng1, CHENG Yun chang2
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| Abstract: |
| This paper studies an accurate identification method for the parameters for a class of linear system, firstly uses PSO (Particle Swarm Optimization) to optimize and iterate the model, chooses suitable deviation standard as the fitness function of the PSO algorithm to iterate the relative parameter speed and size of each particle, on the basis of this, seeks the particle with minimum fitness vale, deducts the optimal fitness function value, implements real time and accurate estimation of systematic parameters and finally uses experiment to test the accuracy and effectiveness of PSO algorithm based parameter identification method. |
| Key words: parameter identification PSO algorithm criterion function |
