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 This email address is being protected from spambots. You need JavaScript enabled to view it. directly.

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