论文标题
对连续时间系统的简化精制仪器变量方法的效率分析
Efficiency Analysis of the Simplified Refined Instrumental Variable Method for Continuous-time Systems
论文作者
论文摘要
在本文中，我们在连续的时间输出误差模型结构中得出了渐近cramér-raO的下限，并提供了基于采样数据的连续时间系统（SRIVC）的简化仪器可变方法的统计效率的分析。它显示出仅依赖于系统的偶然性依赖于系统的噪声范围，该系统仅依赖于系统的相互依赖的噪声范围。 输入。我们还表明，在SRIVC算法的收敛点，估计值不取决于所测量输出的样本间行为。然后证明，在轻度条件下，SRIVC估计量对于输出误差模型结构渐近有效。进行蒙特卡洛模拟以验证SRIVC估计值的渐近cramér-rao下限和渐近协方差。
In this paper, we derive the asymptotic Cramér-Rao lower bound for the continuous-time output error model structure and provide an analysis of the statistical efficiency of the Simplified Refined Instrumental Variable method for Continuous-time systems (SRIVC) based on sampled data.It is shown that the asymptotic Cramér-Rao lower bound is independent of the intersample behaviour of the noise-free system output and hence only depends on the intersample behaviour of the system input. We have also shown that, at the converging point of the SRIVC algorithm, the estimates do not depend on the intersample behaviour of the measured output. It is then proven that the SRIVC estimator is asymptotically efficient for the output error model structure under mild conditions. Monte Carlo simulations are performed to verify the asymptotic Cramér-Rao lower bound and the asymptotic covariance of the SRIVC estimates.
