Introduction to MORE: A MOdel REduction toolbox

In many highly technological engineering fields, the use of dedicated computer-based dynamical system modeling software often leads to large dimensional Linear Time Invariant (LTI) models. These kind of models, composed of a large amount of variables might render drastically inefficient many analysis, control design and optimization techniques. As a matter of fact, considerable attention has been devoted to the development of model reduction - or approximation - techniques to eliminate irrelevant state variables. This paper presents a new freely-available MATLAB©-based toolbox for approximation of medium and large-scale LTI dynamical models, called MORE (MOdel REduction), which implements a collection of very recent advanced algorithms for LTI dynamical model reduction purpose.

[1]  Taishan Zeng,et al.  OPTIMAL H2 MODEL REDUCTION FOR LARGE SCALE MIMO SYSTEMS VIA TANGENTIAL INTERPOLATION , 2011 .

[2]  F. Leibfritz COMPleib: COnstrained Matrix–optimization Problem library – a collection of test examples for nonlinear semidefinite programs, control system design and related problems , 2006 .

[3]  Paul Van Dooren,et al.  H2-optimal model reduction of MIMO systems , 2008, Appl. Math. Lett..

[4]  Robert Skelton,et al.  Model reductions using a projection formulation , 1987, 26th IEEE Conference on Decision and Control.

[5]  Charles Poussot-Vassal,et al.  Generation of a reduced-order LPV/LFT model from a set of large-scale MIMO LTI flexible aircraft models , 2012 .

[6]  Paul Van Dooren,et al.  H2-Optimal Model Reduction with Higher-Order Poles , 2010, SIAM J. Matrix Anal. Appl..

[7]  Roxana Ionutiu,et al.  Passivity-Preserving Model Reduction Using Dominant Spectral-Zero Interpolation , 2008, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[8]  D. Wilson,et al.  Model reduction for multivariable systems , 1974 .

[9]  Paul Van Dooren,et al.  Model Reduction of MIMO Systems via Tangential Interpolation , 2005, SIAM J. Matrix Anal. Appl..

[10]  B. Moore Principal component analysis in linear systems: Controllability, observability, and model reduction , 1981 .

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

[12]  Yousef Saad,et al.  Iterative methods for sparse linear systems , 2003 .

[13]  Charles Poussot-Vassal An iterative SVD-tangential interpolation method for medium-scale MIMO systems approximation with application on flexible aircraft , 2011, IEEE Conference on Decision and Control and European Control Conference.

[14]  Joost Rommes,et al.  Computing Rightmost Eigenvalues for Small-Signal Stability Assessment of Large-Scale Power Systems , 2010, IEEE Transactions on Power Systems.

[15]  Serkan Gugercin,et al.  A trust region method for optimal H2 model reduction , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[16]  A. Antoulas,et al.  H 2 Model Reduction for Large-scale Linear Dynamical Systems * , 2022 .

[17]  Athanasios C. Antoulas,et al.  An overview of model reduction methods and a new result , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

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

[19]  J. Doyle,et al.  Essentials of Robust Control , 1997 .

[20]  K. Glover All optimal Hankel-norm approximations of linear multivariable systems and their L, ∞ -error bounds† , 1984 .

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

[22]  Axel Ruhe Rational Krylov algorithms for nonsymmetric eigenvalue problems. II. matrix pairs , 1994 .

[23]  M. Safonov,et al.  A Schur method for balanced-truncation model reduction , 1989 .

[24]  Serkan Gugercin,et al.  H2 Model Reduction for Large-Scale Linear Dynamical Systems , 2008, SIAM J. Matrix Anal. Appl..

[25]  Serkan Gugercin,et al.  An iterative SVD-Krylov based method for model reduction of large-scale dynamical systems , 2008 .

[26]  M. Safonov,et al.  A Schur Method for Balanced Model Reduction , 1988, 1988 American Control Conference.