Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
720781 | IFAC Proceedings Volumes | 2007 | 6 Pages |
Abstract
Efficient numerical techniques for multivariable system identification and model reduction are investigated. The techniques are implemented in the system identification and model reduction toolboxes based on the Fortran 77 Subroutine Library in Control Theory (SLICOT). Besides highly performant Fortran drivers and computational routines, these toolboxes provide MATLAB or Scilab interfaces, implementing several algorithmic approaches. Extensive numerical testing and comparisons with similar MATLAB tools show that the solvers in these toolboxes are reliable, efficient, and able to solve industrially relevant problems.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Vasile Sima, Peter Benner,