model reduction

model reduction

[′mäd·əl ri′dək·shən]
(control systems)
The process of discarding certain modes of motion while retaining others in the model used by an active control system, in order that the control system can compute control commands with sufficient rapidity.
References in periodicals archive ?
Objective: AdMoRe: Empowered decision-making in simulation-based engineering: Advanced Model Reduction for real-time, inverse and optimization in industrial problems aims at providing in-depth training of Early Stage Researches (ESRs) in the development and application of state-of-the-art computational models and numerical methods to solve cutting-edge engineering problems.
MATHICSE has been one of the leading academic forces in the past ten years on the topic of model reduction, which is the central theme of this CTI project.
2]-optimal model reduction, this can slow down the convergence of iterative algorithms such as IRKA significantly; see [7].
The book then turns to methodological analysis, including structural identifiability, parameter sensitivity, parameter estimation, hypothesis testing, experiment optimization, and model reduction.
Model reduction is warranted and is achieved by grouping rooms into "macro-zones" or clusters of rooms with similar airflow and tracer gas dynamics under varying conditions.
apply model reduction techniques to improve computational speed.
In recent decades a huge number of papers and works have been focused on model reduction of rational approximation of LTI-TDS, see e.
We note that the model reduction and the reduced-order observer design detailed in this paper are discrete-time analogues of the results of Aldeen and Trinh [7] for the observer design of the dominant state of continuous-time linear control systems.
The conference highlighted several main themes, including singular limits; nonlinear wave patterns in multi-dimensions; particle/molecular dynamics; the theory and numerics of multiphases and interfaces; transport in complex environments; and model reduction.
The models differed in approach and age of dogs considered by necessity of the model, number of estimated parameters, or model reduction.
Model reduction techniques are widely used in controller design.

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