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Handling state constraints and economics in feedback control of transport-reaction processes
2015
Journal of Process Control
Preserved Fulltext
Economic model predictive control (EMPC) is a predictive control scheme that combines process economics and feedback control into an integrated framework with the potential of improving the closed-loop ...
The computational efficiency and constraint handling properties of this design are evaluated using a tubular reactor example modeled by two nonlinear parabolic PDEs. ...
Acknowledgments Financial support from the National Science Foundation and the Department of Energy is gratefully acknowledged. ...
doi:10.1016/j.jprocont.2015.04.009
fatcat:f2ntojyqkjgsjcrysbman247iq
2020 Index IEEE Transactions on Automatic Control Vol. 65
2020
IEEE Transactions on Automatic Control
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., +, TAC Jan. 2020 58-71
Robust Economic Model Predictive Control of Continuous-Time Epidemic
Processes. ...
Alghunaim, S.A.,
+, TAC Jan. 2020 175-190
Robust Economic Model Predictive Control of Continuous-Time Epidemic
Processes. ...
Linear programming A Decentralized Event-Based Approach for Robust Model Predictive Control. ...
doi:10.1109/tac.2020.3046985
fatcat:hfiqhyr7sffqtewdmcwzsrugva
Data-driven model reduction-based nonlinear MPC for large-scale distributed parameter systems
2015
Journal of Process Control
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Model Predictive Control (MPC) has been effectively applied in process industries since the 1990s. ...
This paradigm combines elements of gain scheduling, NMPC, model reduction and ANN for effective control of nonlinear DPS. ...
Acknowledgements The authors would like to acknowledge the financial support of the EC FP6 Project: ...
doi:10.1016/j.jprocont.2015.07.009
fatcat:ixwywpxy3bbybdr5xzuu6cb7ay
An efficient reduced-order modeling approach for non-linear parametrized partial differential equations
2008
International Journal for Numerical Methods in Engineering
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The design, optimization, control, and characterization of engineering systems require repeated and real-time output prediction. ...
Our goal is to develop an efficient reduced-order modeling approach for the rapid prediction of functional outputs associated with parametrized PDEs. ...
Patera of MIT and Professor Yvon Maday of the University Paris VI for their many invaluable contributions to this work. ...
doi:10.1002/nme.2309
fatcat:oc55klbsvrbx3ihexips6h3b6q
Modeling Information Diffusion in Online Social Networks with Partial Differential Equations
[article]
2013
arXiv
pre-print
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In a number of recent papers, the authors propose to use partial differential equations(PDEs) to characterize temporal and spatial patterns of information diffusion over online social networks. ...
of the PDE models and highlight the new opportunities and challenges for mathematicians as well as computer scientists and researchers in online social networks. ...
Two of them have been published in [1] and [2] . Spatial models have been used in mathematical biology, sociology, economics, and physics to model spatial-temporal patterns. ...
arXiv:1310.0505v1
fatcat:3ppbt6qmizblbpwmempeb7kizy
Dynamics of CO2 adsorption on sodium oxide promoted alumina in a packed-bed reactor
2011
Chemical Engineering Science
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The model predicted breakthrough curve matches very well with experimental data obtained from a pilot-scale packed-bed reactor. ...
A comprehensive model is developed to describe the coupled transport phenomena and is solved using orthogonal collocation on finite elements. ...
The reduced-order system is then used for model-based control and optimization to enhance process performance. ...
doi:10.1016/j.ces.2011.08.013
fatcat:jzmoux6fxrf5rpea3dbbestqp4
A dynamic theory of spatial externalities
[article]
2021
arXiv
pre-print
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We further provide with a full exploration of the free riding problem and the associated border effect. ...
We characterize the shape of spatial externalities in a continuous time and space differential game with transboundary pollution. ...
3
will also confront the predictions of our game-theoretic model to the abundant empirical
literature counterpart. ...
arXiv:2112.10584v1
fatcat:oj5uzuvfdncjnoiwjzaarp3rbi
State estimation of lithium-ion cells using a physicochemical model based extended Kalman filter
2018
Applied Energy
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state-space representations of the generally accepted physicochemical model (PCM) of a lithium-ion cell are used to estimate local and global states during different charging scenarios. ...
Two different recursive state-observer models using reduced p2D. • Influence of reduction schemes analyzed for estimation process. • Adjusted finite volume method for improved robustness. • Modified EKF ...
The Polynomial and the Eigenfunction approximation are used for the two models implemented in MATLAB (i.e. PPand EM-PCM) beside the benchmark model, which uses the DSI approach. ...
doi:10.1016/j.apenergy.2018.04.011
fatcat:tuf7zke6dfehncvciqcbsznxs4
Fourier's Method of Linear Programming and Its Dual
1986
The American mathematical monthly
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systems
93A15
Large scale systems
93A30
Mathematical modeling (models of systems, model-matching, etc.)
93A99
None of the above, but in this section
93Bxx
Controllability, observability, and system ...
91B52
Special types of equilibria
91B54
Special types of economies
91B55
Economic dynamics
91B60
Trade models
91B62
Growth models
91B64
Macro-economic models (monetary models, models of taxation ...
motions 83C45 Quantization of the gravitational field 83C47 Methods of quantum field theory [See also 81T20] 83C50 Electromagnetic fields 83C55 Macroscopic interaction of the gravitational field with ...
doi:10.2307/2322281
fatcat:yvhgyh2epbcwdoqdhuaopkcrue
Control of moving boundary parabolic partial differential equations (PDEs)
2014
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The second approach is the use of Karhunen-Loève (KL) decomposition to find the empirical eigenfunctions of the solution of moving boundary PDE systems. ...
model of the parabolic PDE system with time-varying domain. ...
Another promising area is the development of advanced control strategies such as Model Predictive Control (MPC) for parabolic PDEs with time-varying domain. ...
doi:10.7939/r3p39h
fatcat:bqfhwyrnrveypmftkrmet4c2t4
Table of contents
2009
2009 17th Mediterranean Conference on Control and Automation
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Two model-based predictive control strategies have been studied: the generalized predictive controller (GPC) and nonlinear adaptive model predictive controller (NAMPC). ...
The controller is implemented using HP-VEE software and Matlab packages. 11:20-11:40 WeA2.6 Adaptive Predictive Control Using Recurrent Neural Network Identification, pp. 61-66 Akpan, Vincent Aristotle ...
The dominant eigenspace of this ensemble is then identified to compute the empirical eigenfunctions required for model reduction. ...
doi:10.1109/med.2009.5164498
fatcat:bi37lbkbhfaihj7lbc64vvplo4
Analytical approximation to the multidimensional Fokker–Planck equation with steady state
2019
Journal of Physics A: Mathematical and Theoretical
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Using asymptotic techniques, that draw upon the known Ornstein--Uhlenbeck (OU) case, we consider a mean-reverting system and obtain its representation as a product of terms, representing short-term, long-term ...
The Fokker--Planck equation is a key ingredient of many models in physics, and related subjects, and arises in a diverse array of settings. ...
Examples include: subatomic particle tracks [9] ; movements in the ionosphere [43] ; chemical reactions [41] ; and extensive use in econometrics for making predictions about financial variables in systems ...
doi:10.1088/1751-8121/aafea3
fatcat:vnfgarkaj5gdrow3fju6u7wah4
Equation-Free, Coarse-Grained Multiscale Computation: Enabling Mocroscopic Simulators to Perform System-Level Analysis
2003
Communications in Mathematical Sciences
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An arsenal of analytical and numerical techniques for the efficient solution of such evolution equations (usually Partial Differential Equations, PDEs) is then brought to bear on the problem. ...
, systems) level. ...
The role of AFOSR (Dynamics and Control, Drs. Jacobs and King), to whom this work was proposed in 1999, and which they supported through the years, has been crucial. ...
doi:10.4310/cms.2003.v1.n4.a5
fatcat:uqxdd6kghje4lnvou7jxfes77m
Turnpike in optimal control of PDEs, ResNets, and beyond
[article]
2022
arXiv
pre-print
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We review a slice of the theory developed over the past decade –the controllability of the underlying system is an important ingredient, and can even be used to devise simple turnpike-like strategies which ...
When formalized mathematically, the turnpike theory corroborates the insights from economics: for an optimal control problem set in a finite-time horizon, optimal controls and corresponding states, are ...
A major part of this work was completed while B.G. was affiliated with the Chair of Computational Mathematics, Fundación Deusto. ...
arXiv:2202.04097v1
fatcat:55e5pbg7ubhqzmuqudjg7kchay
A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems
2015
SIAM Review
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The goal of parametric model reduction is to generate low cost but accurate models that characterize system response for different values of the parameters. ...
Parametric model reduction targets the broad class of problems for which the equations governing the system behavior depend on a set of parameters. ...
of particular parameterized parabolic PDEs [112, 111] ) or a residualbased error indicator [61] . ...
doi:10.1137/130932715
fatcat:lfylrclfjvcxfo7wvxwx6lylb4
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