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Process Modelling and Simulation

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ISBN: 9783039214556 / 9783039214563 Year: Pages: 298 DOI: 10.3390/books978-3-03921-456-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:15
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Abstract

Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.

Keywords

process model validation --- partial least square regression --- phytochemicals --- natural extracts --- wheat germ --- fluidized bed drying --- mathematical model --- moisture content --- condensation --- simulation --- Pharmaceutical Processes --- Mammalian Cell Culture --- sensitivity analysis --- parameter estimation --- Design of Experiments --- algebraic modeling language --- dynamic optimization --- model predictive control --- moving horizon estimation --- fluid bed granulation --- heat and mass balance --- population balance model --- binder dissolution --- kernel development --- robust optimization --- uncertainty --- point estimation method --- equality constraints --- parameter correlation --- barley --- simulation --- hydration --- swelling --- cooking --- porridge --- extents --- graph theory --- model identification --- observability --- optimal clustering --- parameter estimation --- state decoupling --- data-mining --- machine learning --- neural networks --- chemistry --- materials --- engineering --- energy --- grey-box model --- machine learning --- SOS programming --- process modeling --- scrap dissolution --- scrap melting --- thermodynamics --- kinetics --- dynamic converter modelling --- Combined Heat and Power --- gray-box model --- utility management --- CHP legislation --- optimization --- polyacrylonitrile-based carbon fiber --- coagulation bath --- dry-jet wet spinning process --- computational fluid dynamics --- wave resonance --- maximum wave amplitude --- reactor coolant pump --- vane --- costing stopping --- mathematical model --- idling test --- n/a

Control and Nonlinear Dynamics on Energy Conversion Systems

Authors: ---
ISBN: 9783039211104 / 9783039211111 Year: Pages: 438 DOI: 10.3390/books978-3-03921-111-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-08-28 11:21:27
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The ever-increasing need for higher efficiency, smaller size, and lower cost make the analysis, understanding, and design of energy conversion systems extremely important, interesting, and even imperative. One of the most neglected features in the study of such systems is the effect of the inherent nonlinearities on the stability of the system. Due to these nonlinearities, these devices may exhibit undesirable and complex dynamics, which are the focus of many researchers. Even though a lot of research has taken place in this area during the last 20 years, it is still an active research topic for mainstream power engineers. This research has demonstrated that these systems can become unstable with a direct result in increased losses, extra subharmonics, and even uncontrollability/unobservability. The detailed study of these systems can help in the design of smaller, lighter, and less expensive converters that are particularly important in emerging areas of research like electric vehicles, smart grids, renewable energy sources, and others. The aim of this Special Issue is to cover control and nonlinear aspects of instabilities in different energy conversion systems: theoretical, analysis modelling, and practical solutions for such emerging applications. In this Special Issue, we present novel research works in different areas of the control and nonlinear dynamics of energy conversion systems.

Keywords

data-driven --- prediction --- neural network --- air-handling unit (AHU) --- supply air temperature --- pulverizing system --- soft sensor --- inferential control --- moving horizon estimation --- multi-model predictive control --- micro-grid --- droop control --- virtual impedance --- harmonic suppression --- power quality --- combined heat and power unit --- two-stage bypass --- dynamic model --- coordinated control system --- predictive control --- decoupling control --- power conversion --- model–plant mismatches --- disturbance observer --- performance recovery --- offset-free --- electrical machine --- electromagnetic vibration --- multiphysics --- rotor dynamics --- air gap eccentricity --- calculation method --- magnetic saturation --- corrugated pipe --- whistling noise --- Helmholtz number --- excited modes --- switched reluctance generator --- capacitance current pulse train control --- voltage ripple --- capacitance current --- feedback coefficient --- distributed architecture --- maximum power point tracking --- sliding mode control --- overvoltage --- permanent magnet synchronous motor (PMSM) --- single artificial neuron goal representation heuristic dynamic programming (SAN-GrHDP) --- single artificial neuron (SAN) --- reinforcement learning (RL) --- goal representation heuristic dynamic programming (GrHDP) --- adaptive dynamic programming (ADP) --- sliding mode observer (SMO) --- permanent magnet synchronous motor (PMSM) --- extended back electromotive force (EEMF) --- position sensorless --- bridgeless converter --- discontinuous conduction mode (DCM) --- high step-up voltage gain --- power factor correction (PFC) --- space mechanism --- multi-clearance --- nonlinear dynamic model --- planetary gears --- vibration characteristics --- new step-up converter --- ultrahigh voltage conversion ratio --- small-signal model --- average-current mode control --- slope compensation --- monodromy matrix --- current mode control --- boost-flyback converter --- explosion-magnetic generator --- plasma accelerator --- current-pulse formation --- DC-DC buck converter --- contraction analysis --- global stability --- matrix norm --- DC micro grid --- efficiency optimization --- variable bus voltage MG --- variable switching frequency DC-DC converters --- centralized vs. decentralized control --- local vs. global optimization --- buck converter --- DC motor --- bifurcations in control parameter --- sliding control --- zero average dynamics --- fixed-point inducting control --- DC-DC converters --- quadratic boost --- maximum power point tracking (MPPT) --- nonlinear dynamics --- subharmonic oscillations --- photovoltaic (PV) --- steel catenary riser --- rigid body rotation --- wave --- the load of suspension point in the z direction --- Cable3D

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MDPI - Multidisciplinary Digital Publishing Institute (2)


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eng (2)


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2019 (2)