Results 211 to 220 of about 1,287,681 (259)
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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 Stochastic Models
1988 American Control Conference, 1988This paper presents an approach to reduce the order of large-scale stochastic systems. The reduced-order model is obtained by considering only the stable modes through optimization of a steady-state error. Examples are given to illustrate the proposed method.
Craig S. Sims, Ali Feliachi
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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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2014
In this chapter, the full-order state-space models presented in Chap. 3 are reduced in order and parametrized in the main parameters of the flight envelope. Order reduction is achieved by a multistep procedure: A modal reduction is followed by a reduction of the complete aeroelastic model and finally a balanced reduction is performed.
M. Valášek +3 more
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In this chapter, the full-order state-space models presented in Chap. 3 are reduced in order and parametrized in the main parameters of the flight envelope. Order reduction is achieved by a multistep procedure: A modal reduction is followed by a reduction of the complete aeroelastic model and finally a balanced reduction is performed.
M. Valášek +3 more
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Space‐local reduced‐order bases for accelerating reduced‐order models through sparsity
International Journal for Numerical Methods in Engineering, 2022AbstractProjection‐based model order reduction (PMOR) methods based on linear or affine approximation subspaces accelerate numerical predictions by reducing the dimensionality of the underlying computational models. The state of the art of PMOR includes approximation methods based on state‐local subspaces—that is, subspaces associated with different ...
Spenser Anderson +2 more
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2013
This chapter deals with modeling methodologies used for obtaining simplified – in the sense of reduced order – power electronic converter models, which are able to represent their low-frequency average behavior and are more easily employed in simulation or control law design.
Seddik Bacha +2 more
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This chapter deals with modeling methodologies used for obtaining simplified – in the sense of reduced order – power electronic converter models, which are able to represent their low-frequency average behavior and are more easily employed in simulation or control law design.
Seddik Bacha +2 more
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Reduced-Order Models for MEMS Applications
Nonlinear Dynamics, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nayfeh, Ali H. +2 more
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Reduced-order modeling for hyperthermia control
IEEE Transactions on Biomedical Engineering, 1992This paper analyzes the feasibility of using reduced-order modeling techniques in the design of multiple-input, multiple-output (MIMO) hyperthermia temperature controllers. State space thermal models are created based upon a finite difference expansion of the bioheat transfer equation model of a scanned focused ultrasound system (SFUS).
J K, Potocki, H S, Tharp
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Fault Detection Using Reduced Order Models
Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 1993Based on the reduction of dynamic system models, an algebraic redundancy method is proposed which consists of fault detection through the redundant variables and fault diagnosis using a diagnostic matrix. This diagnostic matrix approach, which is an extension of the influence matrix method, is capable of identifying different combinations of failure ...
Daley, S., Wang, H.
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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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