The SLICOT Toolboxes – a Survey

SLICOT is a comprehensive numerical software package for control systems analysis and design. While based on highly performant Fortran routines, Matlab and Scilab interfaces provide convenient access for users. In this survey, we summarize the functionality contained in the three SLICOT toolboxes for (i) basic tasks in systems and control, (ii) system identification, and (iii) model reduction. Several examples illustrate the use of these toolboxes for addressing frequent computational tasks.

[1]  A. Laub.  A schur method for solving algebraic Riccati equations , 1978, 1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes.

[2]  Mei Han An,et al.  accuracy and stability of numerical algorithms , 1991 .

[3]  P. Lancaster,et al.  The Algebraic Riccati Equation , 1995 .

[4]  Andras Varga.  Computation of Kronecker-like forms of a system pencil: applications, algorithms and software , 1996, Proceedings of Joint Conference on Control Applications Intelligent Control and Computer Aided Control System Design.

[5]  A. Varga.  Selection of software for controller reduction. SLICOT Working Note SLWN1999-18 , 1999 .

[6]  Peter Benner,et al.  DAREX - A Collection of Benchmark Examples for Discrete-Time Algebraic Riccati Equations (Version , 1999 .

[7]  Andras Varga.  Selection of Software for Controller Reduction , 1999 .

[8]  Peter Benner,et al.  CAREX - A Collection of Benchmark Examples for Continuous-Time Algebraic Riccati Equations (Version , 1999 .

[9]  D. Sorensen,et al.  A Survey of Model Reduction Methods for Large-Scale Systems , 2000 .

[10]  A. Varga,et al.  Model reduction software in the SLICOT library , 2000, CACSD. Conference Proceedings. IEEE International Symposium on Computer-Aided Control System Design (Cat. No.00TH8537).

[11]  Paul Van Dooren,et al.  Factorizations and linear system solvers for matrices with Toeplitz structure , 2001 .

[12]  Z. Bai.  Krylov subspace techniques for reduced-order modeling of large-scale dynamical systems , 2002 .

[13]  Paul Van Dooren,et al.  A collection of benchmark examples for model reduction of linear time invariant dynamical systems. , 2002 .

[14]  Vasile Sima,et al.  Solving Algebraic Riccati Equations with SLICOT , 2003 .

[15]  R. Freund.  Model reduction methods based on Krylov subspaces , 2003, Acta Numerica.

[16]  Vasile Sima.  Performance investigation of slicot wiener systems identification toolbox , 2003 .

[17]  Sabine Van Huffel,et al.  High-performance numerical algorithms and software for subspace-based linear multivariable system identification , 2004 .

[18]  B. Datta.  Numerical methods for linear control systems : design and analysis , 2004 .

[19]  Athanasios C. Antoulas,et al.  Approximation of Large-Scale Dynamical Systems , 2005, Advances in Design and Control.

[20]  Peter Benner,et al.  Dimension Reduction of Large-Scale Systems , 2005 .

[21]  Andras Varga,et al.  Controller Reduction Using Accuracy-Enhancing Methods , 2005 .

[22]  A. Antoulas,et al.  Special Issue on " Order Reduction of Large-scale Systems " , 2005 .

[23]  Peter Benner,et al.  Numerical Linear Algebra for Model Reduction in Control and Simulation , 2006 .

[24]  Peter Benner,et al.  Evaluation of the Linear Matrix Equation Solvers in SLICOT , 2007 .