Experimental Evidence Showing That Stochastic Subspace Identification Methods May Fail*

نویسنده

  • ANDERS DAHLÉN
چکیده

It is known that certain popular stochastic subspace identification methods may fail for theoretical reasons related to positive realness. In fact, these algorithms are implicitly based on the assumption that the positive and algebraic degrees of a certain estimated covariance sequence coincide. In this paper, we describe how to generate data with the property that this condition is not satisfied. Using this data we show through simulations that several subspace identification algorithms exhibit massive failure.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Identifying Positive Real Models in Subspace Identification by Using Regularization

This paper deals with the lack of positive realness of identified models that may be encountered in many stochastic subspace identification procedures. Lack of positive realness is an often neglected, but important problem. Subspace identification algorithms fail to return a valid linear model if the so-called covariance model, which is obtained from an intermediate realization step in the subs...

متن کامل

On the ill-conditioning of subspace identification with inputs

There is experimental evidence that the performance of standard subspace algorithms from the literature (e.g. the N4SID method) may be surprisingly poor in certain experimental conditions. This happens typically when the past signals (past inputs and outputs) and future input spaces are nearly parallel. In this paper we argue that the poor behavior may be attributed to a form of ill-conditionin...

متن کامل

Subspace Identification of Closed Loop Systems by Stochastic Realization

We develop a closed loop subspace identification method based on stochastic realization theory. Using the preliminary orthogonal decomposition of (Picci and Katayama, 1996b) we show that, under the assumption that the exogenous input is feedback-free and persistently exciting (PE), the identification of closed loop systems is divided into two subproblems: the deterministic identification of the...

متن کامل

Criteria for informative experiments with subspace identification

Informative experiments are identification experiments which contain sufficient information for an identification algorithm to discriminate between different models in an intended model set. In this paper, a particular set of identification algorithms, namely subspace based identification, is considered. Criteria for experiments to be informative with these methods in the deterministic setup an...

متن کامل

Continuous-time subspace system identification using generalized orthonormal basis functions

This paper proposes a new subspace identification algorithm for continuous-time systems using generalized orthonormal basis functions. It is shown that a generalized orthonormal basis induces the transformation of continuoustime stochastic systems into discrete-time stochastic systems, and that the transformed noises have the ergodicity properties. With these basic observations, the standard su...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1998