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An overview of numerically reliable algorithms for model reduction is presented. The covered topics are the reduction of stable and unstable linear systems as well as the computational aspects of frequency weighted model reduction. The presentation of available software tools focuses on a recently developed Fortran library RASP-MODRED implementing a new(More)
We describe recent developments and enhancements of the LFR-toolbox for MATLAB for building LFT-based uncertainty models. A major development is the new LFT-object definition supporting a large class of uncertainty descriptions: continuous- and discrete-time uncertain models, regular and singular parametric expressions, more general uncertainty blocks(More)
The recently developed PERIODIC SYSTEMS Toolbox for MATLAB is described. The basic approach to develop this toolbox was to exploit the powerful object manipulation features of MATLAB via flexible and functionally rich high level m-functions, while simultaneously enforcing highly efficient and numerically sound computations via the mex-function technology of(More)
— We propose a numerically reliable computational approach to design fault detection filters for periodic systems. This approach is based on a new numerically stable algorithm to compute least order annihilators without explicitly building time-invariant lifted system representations. The main computation in this algorithm is the orthogonal reduction of a(More)
We describe the model reduction software developed recently for the control and systems library SLICOT. Besides a powerful collection of Fortran 77 routines implementing the last algorithmic developments for several well-known balancing related methods, we also describe model reduction tools developed to facilitate the usage of SLICOT routines in user(More)
Kronecker-like forms of a system pencil are useful in solving many computational problems encountered in the analysis and synthesis of linear systems. The reduction of system pencils to various Kronecker-like forms can be performed by structure preserving 0(n 3) complexity numerically stable algorithms. The presented algorithms form the basis of a modular(More)
We describe a recently developed Descriptor Systems Toolbox implemented under Matlab. This Toolbox relies on the object oriented approach for control systems analysis and design provided within the standard Control Toolbox of Matlab. The basic approach to develop the Descriptor Systems Toolbox was to exploit the powerful matrix and system object(More)