V. Sima

Proc. CACSD'96 Symposium, Dearborn, MI, pp. 182-187, 1996.

Basic algorithms and LAPACK-based Fortran software for multivariable system identification by subspace techniques are described. Deterministic and combined deterministic-stochastic identification problems are dealt with using two approaches: MOESP (Multivariable Output Error state SPace) and N4SID (Numerical algorithm for Subspace State Space System IDentification). A state space model is computed from input-output data sequences. Multiple data sequences, collected by possibly independent identification experiments, can be handled. Sequential processing of large data sets can be used as an option. Illustrative numerical examples are included.

A. Varga

Proc. 1st MATHMOD Conf., Vienna, pp. 226-230, 1994.

An overview of numerically reliable algorithms for model reduction is presented. The covered topics are the reduction of stable and unstable linear systems as well as the computational aspects of frequency weighted model reduction. The presentation of available software tools focuses on a recently developed Fortran library RASP-MODRED implementing a new generation of numerically reliable algorithms for model reduction.