Numerical integration approach to on-line identification of continuous-time systems
Numerical integration approach to on-line identification of continuous-time systems
复制标题
连续时间系统在线辨识的数值积分方法
DOI：
10.1016/0005-1098(90)90158-e
复制
发表时间：
1990
期刊：
影响因子：
--
通讯作者：
Zhen
中科院分区：
文献类型：
--
作者：
S. Sagara;Zhen
研究了由采样数据估计线性连续微分方程模型参数的问题。使用线性积分滤波器，我们可以得到一个识别模型，直接在连续时间模型参数化。系统的未知初始状态不需要估计。考虑到参数估计的精度和计算量，讨论了采样间隔的选择和线性积分滤波器的设计。将离散时间模型辨识的结果应用于所得到的辨识模型，给出了离散时间参数估计方法，并在特定情况下，明确地推导和讨论了输入一致性的必要条件和充分条件。还包括一个模拟研究，以确认理论结果。
The problem of estimating the parameters in linear continuous differential equation models from sampled data is treated. Using a linear integral filter, we can obtain an identification model that is parametrized directly in the continuous-time model parameters. The unknown initial states of the system do not require estimation. The choice of the sampling interval and the design of the linear integral filter are discussed considering the accuracy of parameter estimates and the computational burden. By applying the results from discrete-time model identification with the obtained identification model, a discrete-time parameter estimation method is developed, and the necessary condition as well as the sufficient condition on the input for consistency are explicitly derived and discussed in particular situations. A simulation study is also included to confirm the theoretical results.