权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Stochastic inverse problems on identification of feedback system

反馈系统辨识的随机反问题

基本信息

批准号：
08680329
负责人：
KISHIDA Kuniharu
金额：
$ 1.34万
依托单位：
Gifu University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1996
资助国家：
日本
起止时间：
1996 至 1998
项目状态：
已结题

项目摘要

In a feedback system described by a stationary Gaussian process open loop transfer functions can be identified under some conditions, where an associate Riccati equation related to an innovation model equivalent to the feedback system has a stable particular solution. The model reduction is also needed for achievement of identification of them. Where the feedback system under the identifiable condition is identified by an autoregressive model, there remains a bias problem due to structure gaps between the original feedback model and the autoregressive model. It is reported that identified open loop transfer functions have a bias of order-dependence of the autoregressive model.From practical applications it is necessary to extend the identification problem of feedback system with the same number of inputs and outputs to that with different number of inputs and outputs. To treat non-square matrices the generalized inverse matrix is used in the generalized Riccati equation, and then the innovation model of non-square feedback system is pseudo-square under a generalized minimum phase condition. The pseudo-square innovation model is studied in a tri-feedback system to understand inconsistency of identification of open loop transfer functions. There are three types of identification problems in the tri-feedback system. From combination of observation variables a scalar type, a vector type and a contracted type of innovation model are studied from the viewpoint of stochastic inverse problem.

在由平稳高斯过程描述的反馈系统中，与反馈系统等效的创新模型相关的关联里卡蒂方程具有稳定的特解，在某些条件下可以识别开环传递函数。为了实现对它们的识别，还需要模型简化。当可辨识条件下的反馈系统被自回归模型识别时，由于原反馈模型与自回归模型之间存在结构间隙，存在偏差问题。据报道，已识别的开环传递函数具有自回归模型的阶依赖偏差。从实际应用来看，有必要将具有相同输入输出数量的反馈系统的辨识问题扩展到具有不同输入输出数量的反馈系统的辨识问题。为了处理非方阵，在广义Riccati方程中引入广义逆矩阵，得到了广义最小相位条件下的非平方反馈系统创新模型为伪平方模型。研究了三反馈系统中的伪平方创新模型，以理解开环传递函数辨识的不一致性。在三反馈系统中有三种类型的辨识问题。从随机逆问题的角度出发，从观测变量的组合出发，研究了标量型、矢量型和收缩型创新模型。