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Reduced-Order Modeling and Filtering
1982In this chapter the purpose is to show how one can find a reduced-order model or a reduced-order filter with a reasonable amount of design effort. It is the author's current feeling that any result which requires the solution of a nonlinear matrix two-point boundary-valued problem of high order, is not practical. The design procedure in such cases will
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2005
Abstract In recent years, reduced-order modeling techniques have proven to be powerful tools for various problems in circuit simulation. For example, today, reduction techniques are routinely used to replace the large RCL subcircuits that model the interconnect or the pin package of VLSI circuits by models of much smaller dimension.
Zhaojun Bai +2 more
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Abstract In recent years, reduced-order modeling techniques have proven to be powerful tools for various problems in circuit simulation. For example, today, reduction techniques are routinely used to replace the large RCL subcircuits that model the interconnect or the pin package of VLSI circuits by models of much smaller dimension.
Zhaojun Bai +2 more
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Laguerre-SVD reduced order modeling
IEEE 8th Topical Meeting on Electrical Performance of Electronic Packaging (Cat. No.99TH8412), 2000A reduced-order modeling method based on a system description in terms of orthonormal Laguerre functions, together with a Krylov subspace decomposition technique is presented. The link with Pade approximation, the block Arnoldi process and singular value decomposition (SVD) leads to a simple and stable implementation of the algorithm. Novel features of
L. Knockaert, D. De Zutter
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REDUCED ORDER MODELS FOR ESTIMATION AND CONTROL
IFAC Proceedings Volumes, 1982Abstract Two methods are discussed for obtaining reduced order models suitable for specific design applications. The first yields a reduced model together with a reduced order Kaiman filter. The second yields a reduced order model together with a partial state-feedback control law.
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Reduced-Order Modeling of Flexible Structures
Journal of Guidance, Control, and Dynamics, 1988An alternate procedure for deriving a reduced-order model is presented. The Routh expansion method is used and preserves the original system impulse response energy. This procedure does not acquire knowledge of the system eigenvalues/eigenvectors and guarantees a stable reduced-order model if the original system is stable.
Ramakrishnan, Jayant V. +2 more
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Reduced order dynamical model for supercapacitors
2010 7th International Conference on Electrical Engineering Computing Science and Automatic Control, 2010A novel dynamical model for a single cell electric double-layer capacitor is proposed. The model was derived from a distributed-parameter electrochemical model, first reformulated and then approximated to reduce its order. Finite dimension approximations were obtained by applying finite differences, finite element and differential quadrature ...
Aldo Romero-Becerril, Luis Alvarez-Icaza
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Reduced-order models for a smart plate
International Journal of Automation and Control, 2007A Single Input Single Output (SISO) state space model has been developed in MATLAB using a smart plate model realised in ANSYS?. The frequency response due to a unit force, for the full model as well as the reduced unsorted and sorted models was studied. DC gain is used as the criterion for sorting.
G. Jayaprasad, C. Sujatha
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A reduced-order modeling of pattern formations.
CoRRChemical and biochemical reactions can exhibit surprisingly different behaviours from multiple steady-state solutions to oscillatory solutions and chaotic behaviours. Such behaviour has been of great interest to researchers for many decades. The Briggs-Rauscher, Belousov-Zhabotinskii and Bray-Liebhafsky reactions, for which periodic variations in ...
Hausenblas, Erika +1 more
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Reduced Order Modelling — Methods and Constraints
2004There is growing attention for methods to reduce the state space dimension of a model, especially in the area of circuit simulation and electromagnetics. Applying these techniques to substructures which behave linearly or weakly non-linearly can dramatically speed up the computations in simulation of complex electronic structures.
Heres, P.J., Schilders, W.H.A.
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Reduced Order Models for Eigenvalue Problems
2006Two main approaches are known for the reduced order modelling of linear time-invariant systems: Krylov subspace based and SVD based approximation methods. Krylov subspace based methods have large scale applicability, but do not have a global error bound.
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