摘要
针对含有未知时滞的多输入单输出动态调节系统,基于过参数化后系统参数向量的稀疏特性,在有限测量数据下,将压缩感知理论和递阶迭代思想相结合,提出一种正交匹配追踪迭代辨识算法。该算法可以辨识多输入动态调节系统的未知时滞、参数和部分阶次。研究结果表明:与最小二乘迭代算法相比,该算法不需要大量的采样数据,可以节约采样成本,提高辨识效率。该算法能够有效地估计这类系统的参数与时滞。
For multiple-input dynamic adjustment systems with unknown time delays, based on the characteristics of sparsity of the over parameterized parameter vector, and by combining the orthogonal matching pursuit algorithm with the hierarchical iterative idea, an orthogonal matching pursuit iterative(OMPI) identification algorithm was presented.This algorithm can estimate the parameters, time delays and some of the orders of the multiple-input dynamic adjustment systems with limited sampled data. The results show that the proposed method can effectively reduce the measuring cost,and improve the identification efficiency since it requires only a small number of sampled data compared to conventional identification methods such as the least square iterative(LSI) method. The proposed algorithm can effectively estimate the parameters and time delays of such sparse systems.
出处
《中南大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2017年第2期389-394,共6页
Journal of Central South University:Science and Technology
基金
国家自然科学基金资助项目(61304138)
江苏省自然科学基金资助项目(BK20130163)~~
关键词
系统辨识
时滞与参数估计
压缩感知
正交匹配追踪
有限采样
system identification
parameter and time delays estimation
compressed sensing
orthogonal matching pursuit algorithm
limited sampled data