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Reduced-Order Modeling

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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Space‐local reduced‐order bases for accelerating reduced‐order models through sparsity

International Journal for Numerical Methods in Engineering, 2022
AbstractProjection‐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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Reduced-Order Averaged Model

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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Reduced-Order Models for MEMS Applications

Nonlinear Dynamics, 2005
zbMATH 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, 1992
This 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, 1993
Based 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

1982
In 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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Reduced-Order Modeling of Flexible Structures

Journal of Guidance, Control, and Dynamics, 1988
An 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 Modelling — Methods and Constraints

2004
There 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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On Synthesis of Reduced Order Models

2011
A framework for model reduction and synthesis is presented, which enables the re-use of reduced order models in circuit simulation. Two synthesis techniques are considered for obtaining the circuit representation (netlist) of the reduced model: (1) by means of realizing the reduced transfer function and (2) by unstamping the reduced system matrices ...
Ionutiu, R., Rommes, J.
openaire   +1 more source

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