Results 51 to 60 of about 31,410,548 (207)
Koopman operator-based model reduction for switched-system control of PDEs [PDF]
at - Automatisierungstechnik, 2017 We present a new framework for optimal and feedback control of PDEs using Koopman operator-based reduced order models (K-ROMs). The Koopman operator is a linear but infinite-dimensional operator which describes the dynamics of observables.
Sebastian Peitz, Stefan Klus
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, 2011 Modelers of molecular signaling networks must cope with the combinatorial explosion of protein states generated by post-translational modifications and complex formations. Rule-based models provide a powerful alternative to approaches that require an explicit enumeration of all possible molecular species of a system [1,2]. Such models consist of formal
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Simple analytic rules for model reduction and PID controller tuning
, 2003 The aim of this paper is to present analytic rules for PID controller tuning that are simple and still result in good closed-loop behavior. The starting point has been the IMC-PID tuning rules that have achieved widespread industrial acceptance. The rule
S. Skogestad
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State-space reduction and equivalence class sampling for a molecular self-assembly model [PDF]
Royal Society Open Science, 2016 Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study.
Daniel M. Packwood +2 more
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Sensors, 2022 This study presents iterative optimal sensor placement (OSP) techniques using the modal assurance criterion (MAC) and the effective independence (EI) algorithm.
Eun-Taik Lee, Hee-Chang Eun
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Approximate MLD System Model of Switched Linear Systems for Model Predictive Control
SICE Journal of Control, Measurement, and System Integration, 2017 In this paper, to reduce the computation time for solving the finite-time optimal control problem (i.e., the model predictive control (MPC) problem), an approximate model of switched linear systems is proposed.
Shin Kanazawa +2 more
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Mathematics, 2023 Transformer-based models for action segmentation have achieved high frame-wise accuracy against challenging benchmarks. However, they rely on multiple decoders and self-attention blocks for informative representations, whose huge computing and memory ...
Zhichao Ma, Kan Li
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Adaptive multiscale model reduction with Generalized Multiscale Finite Element Methods [PDF]
Journal of Computational Physics, 2016 In this paper, we discuss a general multiscale model reduction framework based on multiscale finite element methods. We give a brief overview of related multiscale methods. Due to page limitations, the overview focuses on a few related methods and is not
Eric T. Chung, Y. Efendiev, T. Hou
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The residue of model reduction [PDF]
, 1996 (perhaps omitting quantum mechanics). The significance of this observation for hybrid systems is that the nominal description involving discontinuity is merely a convenient approximation at the relevant time scale which involves the (unmodelled?) neglect of dynamics on any faster time scales — whose details are then necessarily lost in the process of ...
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Dynamic Maximum Entropy Reduction
Entropy, 2019 Any physical system can be regarded on different levels of description varying by how detailed the description is. We propose a method called Dynamic MaxEnt (DynMaxEnt) that provides a passage from the more detailed evolution equations to equations for ...
Václav Klika +3 more
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