This paper examines the problem of estimating linear time-invariant state-space system
models. In particular, it addresses the parametrization and numerical robustness concerns …

This paper addresses the design of gradient-based search algorithms for multivariable
system estimation. In particular, the paper here considers so-called ldquofull …

This paper addresses the problem of estimating the parameters in a multivariable bilinear
model on the basis of observed input-output data. The main contribution is to develop …

The field of control-oriented system identification is mature. Nevertheless, it is still very
active. This is because there are many important unsolved challenges. Of these, this paper …

To control a dynamical system it is essential to obtain an accurate estimate of the current
system state based on uncertain sensor measurements and existing system knowledge. An …

摘要提出了一种辨识线性时不变状态空间系统参数的正交梯度二步递阶优化方法.
通过极小化输出误差目标函数获得了系统参数估计; 提出了正交梯度搜索方法用于解决系统参数 …

A nonlinear optimization-based identification procedure for fully parameterized multivariable
state-space models is presented. The method can be used to identify linear time-invariant …

提出状态空间模型的正交梯度搜索的预报误差辨识方法. 通过极小化输出预报误差而获得系统的
参数估计, 提出了在观测等价类相切面正交子空间进行参数更新的实现方法 …

This paper describes a MATLAB-based software package for estimation of dynamic systems.
A wide range of standard estimation approaches are supported. These include the use of …

Multivariable bilinear state-space systems can be identified by optimizing an output-error
cost function. In this paper a full parameterization of the bilinear system is used. An iterative …