Model Reduction

SLICOT Model and Controller Reduction Toolbox includes SLICOT-based MATLAB and Fortran tools for computing reduced-order linear models and controllers. The toolbox employs theoretically sound and numerically reliable and efficient techniques, including Balance & Truncate, singular perturbation approximation, balanced stochastic truncation, frequency-weighting balancing, Hankel-norm approximation, coprime factorization, etc.

The main functionalities of the toolbox include:

order reduction for continuous-time and discrete-time multivariable models and controllers
order reduction for stable or unstable models/controllers
additive error model reduction
relative error model and controller reduction
frequency-weighted reduction with special stability/performance enforcing weights
coprime factorization-based reduction of state feedback and observer-based controllers

The toolbox main features are:

computational reliability using square-root and balancing-free accuracy enhancing
high numerical efficiency, using latest algorithmic developments, structure exploiting algorithms, and dedicated linear algebra tools
flexibility and easy-of-use
enhanced functionality, e.g, for controller reduction
standardized interfaces

The programs have been extensively tested on various test examples and are fully documented.

SLICOT Toolboxes for MATLAB are subject to a license fee and require an individual license agreement. Find detailed information here or contact the SLICOT Administration directly.

Andras Varga, March 12, 2002, updated Vasile Sima, March 10, 2005