System Realization Using Information Matrix
نویسنده
چکیده
A generalized version of the information matrix is introduced consisting of the autocorrelation and crosscorrelation matrices of the shifted input and output data. Based on the concept of data correlation, a new system realization algorithm is developed to identify a model directly from input and output data. The algorithm starts with computing the information matrix to derive a special correlation matrix that in turn produces the system observabilitymatrix and the state-vector correlation. A systemmodel can then be identi ed from the observability matrix in conjunction with other algebraic manipulations. The algorithm leads to several different methods for computing system matrices to represent the system model. An experimental example is given to illustrate the validity and usefulness of these methods with some comparison.
منابع مشابه
State-Space System Realization With Input- and Output-Data Correlation
This paper introduces a general version of the information matrix consisting of the autocorrelation and cross-correlationmatrices of the shifted input and output data. Based on the concept of data correlation, a new system realization algorithm was developed to create a model directly from input and output data. The algorithm starts by computing a special type of correlation matrix derived from...
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تاریخ انتشار 2003