多输入多输出变量带误差模型的最坏情况频域辨识
Frequency-domain worst-case identification of multiple input multiple output errors-in-variables models

本文将单输入单输出(SISO)变量带误差(EIV)模型的频域最坏情况辨识方法推广应用于多输入多输出 (MIMO)情况. 类似于SISO情况, 多输入多输出变量带误差(MIMO EIV)模型的辨识模型集合由估计的系统名义模型及 其最坏情况误差界描述. 所估计的系统名义模型表征为正规右图符号, 其最坏情况误差界具有可能的更少保守性, 可利 用EIV 模型的先验信息和后验信息由v-gap度量量化得到. 因此, 这种模型集合非常适合于后期利用Vinnicombe提出 的H1回路成形法设计鲁棒控制器. 最后, 利用一数值仿真实例验证所提出辨识方法的有效性.
This paper extends a frequency-domain worst-case identification method for single input single output (SISO) errors-in-variables (EIV) models to its multiple input multiple output (MIMO) case. Similar to the SISO case, the identified model set for a MIMO EIV model is described by an estimated nominal system model and its worst-case error bound. The estimated nominal system model is characterized by a normalized right graph symbol and its worst-case error bound with possibly less conservativeness is quantified by the v-gap metric using a priori and a posteriori information on the EIV model. As a consequence, such model set is well suited to subsequent robust controller design via the H1 loop-shaping method proposed by Vinnicombe. Finally, the proposed identification method is verified by a numerical simulation example.