SLICOT Model and Controller Reduction Toolbox
- 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.
Andras
Varga, March 12, 2002
Updated Vasile
Sima, March 10, 2005
|