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SLICOT-ModelReduction

version 1.0.0 (639 KB) by Andreas Varga
SLICOT Model and Controller Reduction Toolbox

13 Downloads

Updated 24 Jan 2022

From GitHub

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SLICOT Model and Controller Reduction Toolbox

About

The SLICOT Model and Controller Reduction Toolbox (SLICOT-ModelReduction) 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.

Requirements

The codes have been tested with MATLAB 2015b through 2021b. To use the functions, the Control System Toolbox must be installed in MATLAB running under 64-bit Windows 7, 8, 8.1 or 10.

License

  • See LICENSE for licensing information.

References

Please cite SLICOT-ModelReduction using at least one of the following references:

  • A. Varga, Model reduction software in the SLICOT library, In Applied and Computational Control, Signals, and Circuits, Ed. B. Datta, Vol. 2, pp. 239-282, Kluwer Academic Publishers, Boston, 2001.
  • P. Benner, D. Kressner, V, Sima, and A. Varga, The SLICOT Toolboxes - a Survey, SLICOT Working Note 2009-1, August 2009.
  • P. Benner, D. Kressner, V. Sima, and A. Varga, Die SLICOT-Toolboxen für Matlab - The SLICOT Toolboxes for Matlab (in German), at – Automatisierungstechnik, 58 (2010).

Cite As

Andreas Varga (2022). SLICOT-ModelReduction (https://github.com/SLICOT/SLICOT-ModelReduction/releases/tag/v1.0.0), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2021b
Compatible with R2015b to R2021b
Platform Compatibility
Windows macOS Linux

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To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.