distributed parameter

distributed parameter

[di′strib·yəd·əd pə′ram·əd·ər]
(electromagnetism)
References in periodicals archive ?
In distributed parameter model of rail potential and stray current [3,9,12], traction current of each node is obtained from flow calculation of DC traction power system.
A Practical Guide to Geometric Regulation for Distributed Parameter Systems
The model is based directly on the transmission line differential equations represented as the distributed parameter model without any approximation.
He considers it a tool to be used in understanding and treating distributed parameter systems, rather than a sub-discipline of its own.
The issues of distributed parameter systems control were brought to the attention of a professional public at the first IFAC international conference in 1960, where Bellman, (1967) and Pontryagin, (1983) presented their first results.
This method is based on the observation that responses of distributed parameter systems (such as a homogeneous towers, blades etc) can be approximated by a linear combination of a few dominant "modes" of the system.
Examples are presented from distributed parameter systems such as acoustic fields, thermo-dynamic fields, magnetic fields, and vibrations in flexible structures.
It brings together a wide set of material from classical orthogonal function approximation, neural network input-output approximation, finite element methods for distributed parameter systems, and various approximation methods used in adaptive control and learning theory.
In the MPC formulation, the state variables of a non-linear distributed parameter model used are lumped via the finite difference method.
Instead of fighting the problems of geometry and parasitics, a distributed parameter approach was devised.
Thus process-based, distributed parameter, continuous simulation erosion prediction model has been used successfully in a variety of applications.
Zhao (both of Ohio State University) presented a possible application of spatial aggregation for the description and interpretation of distributed parameter physical fields, whereas Yip (Massachusetts Institute of Technology) highlighted the descriptive potential of spatial aggregation in interpreting fluid-flow simulation data by extracting three-dimensional structures, classifying them, and analyzing their spatial and temporal coherence.

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