New Numerical Software for Model and Controller Reduction

Abstract

In this report we describe the recently developed model and controller reduction software for SLICOT within Task II.B of the NICONET Project. A powerful collection of user callable Fortran 77 routines has been implemented based on the latest algorithmic developments which cover the relative error model reduction using the balanced stochastic truncation approach, model reduction using frequency-weighted balancing and frequency-weighted Hankel-norm approximation methods, as well as special controller reduction methods using frequency-weighted balancing and coprime factorization based techniques. All implemented routines can be employed to reduce both stable and unstable, continuous- or discrete-time models or controllers. The underlying numerical algorithms are based on extensions of the square-root and balancing-free accuracy enhancing technique developed by the author for balancing-related model reduction. The new model and controller reduction routines for SLICOT are among the most powerful and numerically most reliable software tools available for model and controller reduction. To facilitate their usage, easy-to-use and flexible interface have been developed to integrate them in MATLAB and Scilab.