An acceleration for the eigensystem realization algorithm with partial singular values decomposition

The real-time identification of dynamic parameters is important for the control system of spacecraft. The eigensystem realization algorithm (ERA) is currently the typical method for such application. In order to identify the dynamic parameter of spacecraft rapidly and accurately, an accelerated ERA with a partial singular values decomposition (PSVD) algorithm is presented. In the PSVD, the Hankel matrix is reduced to dual diagonal form first, and then transformed into a tridiagonal matrix. The eigenvalues are computed by the bisection method in terms of the Sturm property, and the corresponding eigenvectors are obtained by the inverse iteration method. Finally, the eigenvalues and the eigenvectors are transformed into the singular values and the singular value vectors of the original matrix. An example for space station is presented to demonstrate the efficacy and accuracy of the proposed algorithm.