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检索条件"任意字段=Symposium on Dynamics and Control of Process Systems"

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Hybrid modeling approach for terpolymerization reactions in CSTR 13th

Hybrid modeling approach for terpolymerization reactions in ...

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13th IFAC symposium on dynamics and control of process systems, including Biosystems, DYCOPS 2022

作者： Lee, Kyoungmin Choi, Suk Hoon Lee, Jong Min School of Chemical and Biological Engineering Institute of Chemical Process Seoul National University Seoul08826 Korea Republic of

In order to produce terpolymer of desired quality a model capable of simulating terpolymerization is required. Terpolymerization involves complex reactions, full-scale modeling using the frst principle model is not practical to simulate reaction because there are many parameters to be estimated. In this study, a hybrid model that integrates the frst-principles model and the DNN model is proposed. The proposed hybrid model reduces the parameters that need to be estimated using a cumulative composition model, through the steady-state assumption. Afterward, DNN model in a hybrid model estimates the conversion using measurement data from process sensors, and the terpolymer composition according to conversion is calculated. In the process, by estimating model parameters with error in variables model, hybrid model specifc to the system is constructed. Validation of the hybrid model is performed using measurement data of 600 days and the result shows a good agreement with the actual data. The proposed hybrid model has high fdelity, scalability and robustness to other terpolymerization process. © 2022 Elsevier B.V.. All rights reserved.

关键词： Deep neural networks

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A Simulation Study on Model-Based Optimization of Intracellular Trehalose Accumulation in Saccharomyces cerevisiae Fed-Batch Cultures 13th

A Simulation Study on Model-Based Optimization of Intracellu...

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13th IFAC symposium on dynamics and control of process systems, including Biosystems (DYCOPS)

作者： Sbarciog, Mihaela Huet, Antoine Bogaerts, Philippe Univ Libre Bruxelles 3BIO BioControl CP 165-6150 Av FD Roosevelt B-1050 Brussels Belgium

Trehalose is a reserve carbohydrate, which occurs naturally in yeast and acts as a stress protectant for cells. Due to its features, trehalose is used in many industries (food, biopharmaceuticals, cosmetics). Its production/accumulation may be triggered and enhanced by the culture operating conditions, among which the feed flow rate and the start of the starvation period play the most important role. This paper presents a simulation study based on a novel model validated with experimental data, highlighting the interplay between trehalose maximization and biomass maximization. Several single-objective and multi-objective constrained optimization problems are solved using the control vector parameterization approach. It is shown that maximizing either the trehalose concentration or the biomass amount leads to solutions which are not appealing in practice. The best solution is obtained by maximizing trehalose concentration with a lower bound on the biomass amount. A comparison of the optimal solution to experimental data reveals that, although approximately the same amount of biomass can be obtained with different feeding profiles and starvation times, the maximization of trehalose concentration requires feeding most of the culture medium in the first part of the experiment while starting the nitrogen starvation at an early stage. Copyright (C) 2022 The Authors.

关键词： Saccharomyces cerevisiae trehalose dynamical model process optimization control vector parameterization stress protectant

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Modeling and process Operability Analysis o f a Direct Air Capture System 13th

Modeling and Process Operability Analysis o f a Direct Air C...

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13th IFAC symposium on dynamics and control of process systems, including Biosystems (DYCOPS)

作者： Gama, Vitor V. Dinh, San Alves, Victor Dantas, Beatriz N. A. Bishop, Brent A. Lima, Fernando, V West Virginia Univ Morgantown WV 26506 USA Univ Fed Campina Grande Campina Grande Paraiba Brazil

The climate crisis has become an important subject of study since it has impacted every single life on the planet. Aggravated by the large amounts of carbon dioxide released to the atmosphere, such crisis has influenced environmental regulations around the world. To lower the accumulation of this greenhouse gas in the atmosphere, several new technologies are currently being explored in the field of carbon capture and sequestration. This research focuses primarily on Direct Air Capture (DAC) technologies since they have advantages such as ease in installing and placing their facilities. Thus, the capture could be carried out near energy sources and storage sites, hence reducing costs and emissions especially of geographically remote CO2 producing processes. The DAC system design can be customized to meet the desired CO2 specifications in the captured product. In this work, a 3-stage membrane module arrangement for DAC is chosen due to its CO2 separation capabilities. A novel framework based on operability analysis is also employed to find a feasible design region for the DAC system that can operate at different pollution levels. The system is simulated employing AVEVA process Simulation (an equation-oriented software) coupled with a Python script interface as well as MATLAB to perform process operability calculations. The results show that a feasible design for DAC can be successfully established with the proposed framework accounting for product and byproduct impurities. Copyright (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license(https://***/licenses/by-nc-nd/4.0/)

关键词： Carbon Capture Membrane Module process Operability AVEVA process Simulation

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Hamiltonian-Based control Approach with Pendulum Application

Hamiltonian-Based Control Approach with Pendulum Application

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International symposium on Applied Computational Intelligence and Informatics ( SACI)

作者： Claudiu Pozna Radu-Emil Precup Aron Ballagi Department of Automation Széchenyi István University Győr Hungary Dept. Autom. Inform. Technol. Transilvania University of Brasov Brasov Romania Dept. Automation and Applied Informatics Politehnica University of Timisoara Center Fundam. Adv. Tech. Res. Romanian Academy - Timisoara Branch Timisoara Romania

ISBN: (数字)9798350329520

ISBN: (纸本)9798350329537

The paper proposes a design method dedicated to control systems, which use a certain energy function (surface), called the Hamiltonian of the system. The plant requires, most of the time, the convergence at different fixed points and at the same time in different ways (different behaviors). This phenomenon is possible by modifying the initial energy surface. Modification of the energy surface can be achieved by external (generalized) forces. The formalism suggested in this paper allows the calculation of generalized forces and, finally, to obtain the mentioned changes.

关键词： Potential energy Design methodology process control Mathematical models Vectors Trajectory Vehicle dynamics

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Fitting nonlinear models to continuous oxygen data with oscillatory signal variations via a loss based on Dynamic Time Warping 13th

Fitting nonlinear models to continuous oxygen data with osci...

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13th IFAC symposium on dynamics and control of process systems, including Biosystems (DYCOPS)

作者： Aizpuru, Judit Kemmer, Annina Karolin Kim, Jong Woo Born, Stefan Neubauer, Peter Bournazou, Mariano N. Cruz Barz, Tilman Tech Univ Berlin Chair Bioproc Engn Str 17 Juni 135 D-10623 Berlin Germany DataHow AG Zurichstr 137 CH-8600 Dubendorf Switzerland AIT Austrian Inst Technol GmbH Ctr Energy Giefingasse 2 A-1210 Vienna Austria

High throughput experimental systems play an important role in bioprocess development, as they provide an efficient way of analysing different experimental conditions and perform strain discrimination in previous phases to the industrial scale production. In the millilitre scale, these systems are combinations of parallel mini-bioreactors, liquid handling robots and automated workflows for data handling and model based operation. For successfully monitoring cultivation conditions and improving the overall process quality by model-based approaches, a proper model identification is crucial. However, the quality and amount of measurements makes this task challenging considering the complexity of the bio-processes. The Dissolved Oxygen Tension is often the only measurement which is available online, and therefore, a good understanding of the errors in this signal is important for performing a robust estimation. Some of the expected errors will provoke uncertainties in the time-domain of the measurement, and in those cases, the common Weighted Least Squares estimation procedure can fail providing good results. Moreover, these errors will have even a larger effect in the fed-batch phase where bolus feeding is applied, as this generates fast dynamic responses in the signal. In the present work, an insilico study of the performance of Weighted Least Squares estimator is analysed when the expected time-uncertainties are present in the oxygen signal. As an alternative, a loss based on the Dynamic Time Warping measure is proposed. The results show how this latter procedure outperforms the former reconstructing the oxygen signal, and in addition, returns less biased parameter estimates. Copyright (C) 2022 The Authors.

关键词： Dissolved Oxygen Tension Nonlinear system identification Dynamic time warping Estimation and control in biological systems Time series modelling

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Prairie Dog Optimization-based Tilt-Integral-Derivative controller for Frequency Regulation of Power System

Prairie Dog Optimization-based Tilt-Integral-Derivative Cont...

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International Artificial Intelligence and Data processing symposium (IDAP)

作者： Serdar Ekinci Davut Izci Laith Abualigah Raymond Ghandour Mohammad Salman Department of Computer Engineering Batman University Batman Turkey Computer Science Department MEU Research Unit Middle East University Amman Jordan College of Engineering and Technology American University of the Middle East Kuwait

ISBN: (数字)9798331531492

ISBN: (纸本)9798331531508

The load frequency control (LFC) system is the primary subject of this investigation because of the critical role it plays in regulating both the generation and demand of electrical power. It is becoming increasingly important to ensure that the LFC system is implemented with precision as the level of uncertainty surrounding renewable energy sources and altering demand patterns continues to increase. An investigation into the dynamics of low-frequency converters (LFC) in a hybrid power system that functions in two domains and is comprised of a photovoltaic (PV) system and a reheat thermal system is the focus of this scientific study. The implementation of a tilt-integral-derivative (TID) controller is done in order to improve the performance of the system. In addition, the paper provides a description of the process by which the controller settings were adjusted by employing a one-of-a-kind optimization technique known as the Prairie dog optimizer (PDO). There has been no investigation into the use of this approach in LFC designs. It is an integral of time-multiplied absolute error (ITAE) that serves as the objective function of the optimization approach. A comparison is made between the performance of the PDO-tuned TID controller and other established strategies that have been published in recent literature. A decrease in overshoot values and an improvement in damping durations for both system frequency and tie-line power fluctuations are two of the evidences that demonstrate that the suggested strategy is superior to the methodologies that are currently in use. The results reveal that the proposed strategy is superior.

关键词： Photovoltaic systems Time-frequency analysis Grasslands Renewable energy sources Fluctuations Uncertainty Power system dynamics process control Dogs Hybrid power systems

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Optimization of the dynamic regulation in a branch-in metabolic pathway 13th

Optimization of the dynamic regulation in a branch-in metabo...

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13th IFAC symposium on dynamics and control of process systems, including Biosystems (DYCOPS)

作者： Boada, Y. Santos-Navarro, F. N. Vignoni, A. Pico, J. Univ Politecn Valencia IU Automat & Informat Ind ai2 Synthet Biol & Biosyst Control Lab Camino Vera S-N E-46022 Valencia Spain

Multiobjective optimization has already been shown to be an appropriate tool to characterize and tune systems subject to multiple trade-offs among competing objectives. Here, we consider the dynamic regulation of a merging metabolic pathway motif. This motif appears in a wide range of metabolic engineering applications, including the production of phenylpropanoids highly appreciated by the pharma, nutraceutical and the cosmetic industries. We present an approach to use multiobjective optimization for the optimal tuning of the gene circuit parts composing the biomolecular controller and biosensor in the dynamic regulation of the metabolic pathway. We show how this approach can deal with the trade-offs between performance of the regulated pathway, robustness with respect to perturbations, and stability of the feedback loop. Our results suggest that the strategies for fine-tuning the trade-offs among performance, robustness, and stability in dynamic pathway regulation are complex and it is not always possible to infer them by simple inspection. This renders the use of the multiobjective optimization methodology not only useful but necessary. Copyright (C) 2022 The Authors.

关键词： Synthetic biology gene circuits metabolic pathways multiobjective optimization dynamic regulation

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Reaching Optimal Distributed Estimation Through Myopic Self-Confidence Adaptation 25th

Reaching Optimal Distributed Estimation Through Myopic Self-...

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25th International symposium on Mathematical Theory of Networks and systems (MTNS)

作者： Como, Giacomo Fagnani, Fabio Proskurnikov, Anton, V Politecn Torino Dept Math Sci GL Lagrange I-10129 Turin Italy Politecn Torino Dept Elect & Telecommun I-10129 Turin Italy

Consider discrete-time linear distributed averaging dynamics, whereby a finite number of agents in a network start with uncorrelated and unbiased noisy measurements of a common state of the world modeled as a scalar parameter, and iteratively update their estimates following a non-Bayesian learning rule. Specifically, let every agent update her estimate to a convex combination of her own current estimate and those of her neighbors in the network (this procedure is also known as the French-DeGroot model, or the consensus algorithm). As a result of this iterative averaging process, each agent obtains an asymptotic estimate of the state of the world, and the variance of this individual estimate depends on the matrix of weights the agents assign to themselves and to the others. We study a game-theoretic multi-objective optimization problem whereby every agent seeks to choose her self-confidence value in the convex combination in such a way to minimize the variance of her asymptotic estimate of the state of the world. Assuming that the relative influence weights assigned by the agents to their neighbors in the network remain fixed and form an irreducible relative influence matrix, we characterize the Pareto frontier of the problem, as well as the set of Nash equilibria in the resulting game. Copyright (C) 2022 The Authors.

关键词： Games on graphs centrality measures opinion dynamics

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Understanding Fluid Exchange as Screens are Run in Hole - Mitigation of Formation and Completion Damage Risks

Understanding Fluid Exchange as Screens are Run in Hole - Mi...

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2022 SPE International Conference and Exhibition on Formation Damage control, FD 2022

作者： Byrne, Michael Djayapertapa, Lesmana Watson, Ken Fleming, Niall Taugbøl, Knut Axis Equinor

ISBN: (纸本)9781613998373

To reduce the risk of screen plugging with drilling fluid solids, wellbore fluids are typically displaced to low or no solids systems before sand screen lower completions are run in to wells. Displacing the entire wellbore volume to low solids fluids can add significant cost particularly in high pressure wells. An option can be to displace the open hole section of the well only with the low solids fluid and run the lower completion through the original drilling fluid. A refinement of this process is to fill the upper hole section with the low solids fluid in order to pre-saturate the screens assembly. The movement or exchange of the two fluids as the screens are run in to the wellbore has been a significant uncertainty, until now! This work was conducted to investigate the potential for fluids to exchange as sand screen completions are run in to wells in the Field 1 Satellite and Field 2 developments. The hypothesis that fluids in the wellbore would displace fluids inside the screen assembly as the screens are run in to the well was tested. Computational Fluid dynamics (CFD) modelling was used to simulate the movement of the lower completion in to the well and determine the rate and quantity of fluid exchange. The simulations demonstrated that when stand alone screen (SAS) completions are run in to wellbores, fluids will exchange from outside to inside the screens. This process happens at all tripping speeds examined and in all parts of the cased and open hole wellbore. The fluid exchange continues throughout the running in process, including in the open hole lower completion. There is no value in filling the top hole section with low solids completion fluid unless fluid exchange during running in can be controlled. When a one-way inflow control device (ICD) check valve is fitted to each screen joint allowing fluid to flow in to the tubing but not back out to the annulus then fluid exchange is significantly limited. Careful consideration should be given to the excha

关键词： Computational fluid dynamics

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Learning the Optimal controller Placement in Mobile Software-Defined Networks 23

Learning the Optimal Controller Placement in Mobile Software...

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23rd IEEE International symposium on a World of Wireless, Mobile and Multimedia Networks (IEEE WoWMoM)

作者： Koutsopoulos, Iordanis Athens Univ Econ & Business Dept Informat Athens Greece

ISBN: (数字)9781665408769

ISBN: (纸本)9781665408769

We formulate and study the problem of online learning of the optimal controller selection policy in mobile SoftwareDefined Networks, where the controller-switch round-trip-time (RTT) delays are unknown and time-varying. Static optimization approaches are not helpful, since delays vary significantly (and sometimes, arbitrarily) from one slot to another, and only RTT delays from the current active controller can be easily measured. First, we model the sequence of RTT delays across time as a stationary random process so that the value at each time slot is a sample from an unknown probability distribution with unknown mean. This approach is applicable in relatively static network settings, where stationarity can be assumed. We cast the problem as a stochastic multiarmed bandit, where the arms are the different controller choices, and we fit different bandit algorithms to that setting, such as: the Lowest Confidence Bound (LCB) algorithm by modifying the known Upper Confidence Bound (UCB) one, the LCB-tuned one, and the Boltzmann exploration one. The first two are known to achieve sublinear regret, while the last one turns out to be very efficient. In a second approach, the random process of RTTs is non-stationary and thus cannot be characterized statistically. This scenario is applicable in cases of arbitrary mobility and other dynamics that affect RTT delays in an unpredictable, adversarial manner. We pose the problem as an adversarial bandit that can be solved with the EXP3 algorithm which achieves sublinear regret. We argue that all approaches can be implemented in an SDN environment with lightweight messaging. We also compare the performance of these algorithms for different problem settings and hyper-parameters that reflect the efficiency of the learning process. Numerical evaluation shows that Boltzmann exploration achieves the best performance.

关键词： Wireless communication Uncertainty Stochastic processes Switches control systems Probability distribution Delays

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