Conferences related to Crystallizers

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2020 American Control Conference (ACC)

The ACC is the annual conference of the American Automatic Control Council (AACC, the U.S. national member organization of the International Federation for Automatic Control (IFAC)). The ACC is internationally recognized as a premier scientific and engineering conference dedicated to the advancement of control theory and practice. The ACC brings together an international community of researchers and practitioners to discuss the latest findings in automatic control. The 2020 ACC technical program will

  • 1996 13th Triennial World Congress of the International Federation of Automatic Control (IFAC)

  • 1997 American Control Conference - ACC '97

  • 1998 American Control Conference - ACC '98

  • 1999 American Control Conference - ACC '99

  • 2000 American Control Conference - ACC 2000

  • 2001 American Control Conference - ACC 2001

  • 2002 American Control Conference - ACC 2002

  • 2003 American Control Conference - ACC 2003

  • 2004 American Control Conference - ACC 2004

  • 2005 American Control Conference - ACC 2005

  • 2006 American Control Conference - ACC 2006 (Silver Anniversary)

  • 2007 American Control Conference - ACC 2007

  • 2008 American Control Conference - ACC 2008

  • 2009 American Control Conference - ACC 2009

    The 2009 ACC technical program will cover new developments related to theory, application, and education in control science and engineering. In addition to regular technical sessions the program will also feature interactive and tutorial sessions and preconference workshops.

  • 2010 American Control Conference - ACC 2010

    Theory and practice of automatic control

  • 2011 American Control Conference - ACC 2011

    ACC provides a forum for bringing industry and academia together to discuss the latest developments in the area of Automatic Control Systems, from new control theories, to the advances in sensors and actuator technologies, and to new applications areas for automation.

  • 2012 American Control Conference - ACC 2012

    All areas of control engineering and science.

  • 2013 American Control Conference (ACC)

    Control systems theory and practice. Conference themes on sustainability, societal challenges for control, smart healthcare systems. Conference topics include biological systems, vehicle dynamics and control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2014 American Control Conference - ACC 2014

    All areas of the theory and practice of automatic control, including but not limited to network control systems, model predictive control, systems analysis in biology and medicine, hybrid and switched systems, aerospace systems, power and energy systems and control of nano- and micro-systems.

  • 2015 American Control Conference (ACC)

    control theory, technology, and practice

  • 2016 American Control Conference (ACC)

    Control systems theory and practice. Conference topics include biological systems, vehicle dynamics and control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2017 American Control Conference (ACC)

    Technical topics include biological systems, vehicle dynamics and control, adaptive control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2018 Annual American Control Conference (ACC)

    Technical topics include biological systems, vehicle dynamics and control, adaptive control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2019 American Control Conference (ACC)

    Technical topics include biological systems, vehicle dynamics and control, adaptive control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.


2020 22nd European Conference on Power Electronics and Applications (EPE'20 ECCE Europe)

Energy conversion and conditioning technologies, power electronics, adjustable speed drives and their applications, power electronics for smarter grid, energy efficiency,technologies for sustainable energy systems, converters and power supplies


2020 59th IEEE Conference on Decision and Control (CDC)

The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.


2019 International Joint Conference on Neural Networks (IJCNN)

IJCNN covers a wide range of topics in the field of neural networks, from biological neural network modeling to artificial neural computation.


2019 IEEE 15th International Conference on Control and Automation (ICCA)

The 15th IEEE International Conference on Control and Automation (IEEE ICCA 2019) will be held Tuesday through Friday, July 16-19, 2019, in Edinburgh, Scotland. The conference is jointly organized by IEEE Control Systems Chapter, Singapore, and IEEE Control Chapter for United Kingdom and Ireland. It is technically sponsored by IEEE Control Systems Society. It aims to create a forum for scientists and practising engineers throughout the world to present the latest research findings and ideas in the areas of control and automation, and possible contributions toward sustainable development and environment preservation. The conference is featured with the Best Paper Award and the Best Student Paper Award.



Periodicals related to Crystallizers

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Control Systems Technology, IEEE Transactions on

Serves as a compendium for papers on the technological advances in control engineering and as an archival publication which will bridge the gap between theory and practice. Papers will highlight the latest knowledge, exploratory developments, and practical applications in all aspects of the technology needed to implement control systems from analysis and design through simulation and hardware.


Nuclear Science, IEEE Transactions on

All aspects of the theory and applications of nuclear science and engineering, including instrumentation for the detection and measurement of ionizing radiation; particle accelerators and their controls; nuclear medicine and its application; effects of radiation on materials, components, and systems; reactor instrumentation and controls; and measurement of radiation in space.



Most published Xplore authors for Crystallizers

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Xplore Articles related to Crystallizers

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Notice of Retraction<br>The study of crack forecast with continuous casting based on illegibility analysis

2010 International Conference on Computer and Communication Technologies in Agriculture Engineering, 2010

This article has been retracted by the publisher.


Detection of phases in sugar crystallization using wavelets

Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001

This paper presents an approach to the automatic supervision of the sugar crystallization process based on image-processing techniques. The detection of the different phases of the process is carried out by generating patterns from a wavelet decomposition of the microscopic images taken from the process.


Optimal coordination of crystallization batch processes using rules and practices of extreme programming

Proceedings of 2003 IEEE Conference on Control Applications, 2003. CCA 2003., 2003

This contribution describes the development and implementation of a complex control system for a sugar production plant. Using practices of extreme programming control algorithms have been generated to realize an optimal coordination of twenty batch crystallizers. Thus the equilibrium of mass and energy flows as well as the improvement of sugar quality parameters could be achieved. The developed batch control ...


Modeling and optimization of struvite precipitation process for phosphorus recovery from wastewater

2011 Fourth International Conference on Modeling, Simulation and Applied Optimization, 2011

The recovery of phosphorus from wastewater following struvite precipitation pathway can provide a viable and sustainable source for phosphorus. This pathway is important because current phosphorus ore reserves are expected to be exhausted within the next few decades, or, the recovery from the ores will become more costly. However, the recovery of phosphorus from wastewater is not straightforward due to ...


Modeling and optimization of continuous crystallization using a continuous oscillatory baffled crystallizer

2018 Chinese Control And Decision Conference (CCDC), 2018

In this paper, the continuous crystallization process with a continuous oscillatory baffled crystallizer (COBC) has been studied. The control objective is to obtain the desired crystal size distribution (CSD) from this process. A population balance equation (PBE) is derived by combining the crystallization mechanism and the COBC structure characteristics. The solution of the PBE can be used to characterize the ...



Educational Resources on Crystallizers

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IEEE.tv Videos

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IEEE-USA E-Books

  • Notice of Retraction<br>The study of crack forecast with continuous casting based on illegibility analysis

    This article has been retracted by the publisher.

  • Detection of phases in sugar crystallization using wavelets

    This paper presents an approach to the automatic supervision of the sugar crystallization process based on image-processing techniques. The detection of the different phases of the process is carried out by generating patterns from a wavelet decomposition of the microscopic images taken from the process.

  • Optimal coordination of crystallization batch processes using rules and practices of extreme programming

    This contribution describes the development and implementation of a complex control system for a sugar production plant. Using practices of extreme programming control algorithms have been generated to realize an optimal coordination of twenty batch crystallizers. Thus the equilibrium of mass and energy flows as well as the improvement of sugar quality parameters could be achieved. The developed batch control is working on the level of process coordination, acting directly on the level of process control. All algorithms are implemented in Matlab/Simulink and handle about 300 binary and continuous I/O-signals in real time connection. Therefore a client server structure is established between Matlab and the process control system.

  • Modeling and optimization of struvite precipitation process for phosphorus recovery from wastewater

    The recovery of phosphorus from wastewater following struvite precipitation pathway can provide a viable and sustainable source for phosphorus. This pathway is important because current phosphorus ore reserves are expected to be exhausted within the next few decades, or, the recovery from the ores will become more costly. However, the recovery of phosphorus from wastewater is not straightforward due to the complexities arising from the number of variables and chemistry involved with the precipitation of phosphorus as struvite. Modeling the dynamic nature of the crystallization phenomenon appears to be the method of choice to control the process. In this study, a dynamic control model for phosphorus recovery process via struvite crystallization was developed. This model incorporated both chemistry and control software, and was used to increase the efficiency and ease of process operation of a pilot- scale fluidized crystallizer. This process model was the basis of an automatic controller that had the capability to manipulate flows and chemical additions, and thereby control the system at a desired set point. The control model was then used as a prediction tool to determine conditions that influence the supersaturation ratio - the primary control parameter - of the process.

  • Modeling and optimization of continuous crystallization using a continuous oscillatory baffled crystallizer

    In this paper, the continuous crystallization process with a continuous oscillatory baffled crystallizer (COBC) has been studied. The control objective is to obtain the desired crystal size distribution (CSD) from this process. A population balance equation (PBE) is derived by combining the crystallization mechanism and the COBC structure characteristics. The solution of the PBE can be used to characterize the CSD of any given position within the crystallizer. Constant supersaturation control has been chosen to control the crystallization process and the optimal supersaturation value is obtained by minimizing the error between the desired and the calculated CSDs, which leads to the desired cooling temperature profile along the crystallizer. The inlet temperature of the cooling water of the jacketed glass tubes is calculated based on energy balance which ensures that the solution temperature along the crystallizer follows the desired cooling temperature curve. A set of simulations has been provided to demonstrate the effectiveness of proposed method.

  • Model Identification and Control Strategies for Batch Cooling Crystallizers

    The study of an optimal cooling control strategy for a batch white sugar crystallization process is reported in this paper. Within the proposed control strategy, a dynamic optimization algorithm (DOA) and a generic model control (GMC) algorithm were compared with respect to the final process quality achieved. The linear models required in the controller structures were extracted applying two identification alternatives. The GMC algorithm cases seem to guarantee more satisfactory end point quality of the process. However, only the DOA of the supersaturation manipulating the steam flowrate makes feasible all conflicting control objectives.

  • Intelligent prediction method of quality for continuous casting process

    Quality prediction of casting billet in continuous casting process has great significance on ensuring the continuity of production and improving the quality of casting billet. The process parameters have influence on the quality of casting billet in continuous casting process, so this paper proposes an intelligent prediction method of casting quality based on multiple process parameters. Through the analysis of the relationship between multiple process parameters and the casting quality, the casting quality prediction model based on least squares support vector machine (LSSVM) is established. And an improved particle swarm optimization (iPSO) algorithm is used to optimize the parameters of the prediction model. Then the quality prediction of casting billet under different combinations of process parameters could be implemented. In the continuous casting grade transition process, the proposed method in this paper is used to establish the prediction model of the intermixing length. The results of the case prove the effectiveness of the proposed method.

  • Inferential modeling in pharmaceutical crystallization

    The main limitation to improving the online operation of crystallization processes for the past twenty years has been the lack of reliable and informative real-time sensors. Inferential models are developed to fill this need. The inferential modeling problem for these processes is especially challenging due to the low quantity of data relative to the dimensionality of the measurement vector that serves as the input to the inferential model. Quantifying prediction intervals is critical in these applications, which involves more sophisticated chemometric analysis techniques than those popular in the process control literature. The principles and techniques are illustrated through application to the batch crystallization of a pharmaceutical chemical.

  • Combined water seam crystallizer's thermal field analysis and simulation

    According to the complexity of Crystallizer's heat-transferring in continuous casting engineering, it is very difficult to identify and analyze the Crystallizer's temperature field. Based on classical theory, this paper's aim is to seized the conditions which can portrait the major factor in the problem, then, to establish mathematical and physical models to explore and analysis the mold's heat transferring phenomenon. According to the actual conditions, we can determine the relevant parameters, and give two different models element simulation analysis. The results can be used by the heat- transferring structure designer and can provide some theoretical basis and reference materials for Crystallizer's monitoring.

  • Monitoring of continuous crystallization process

    Monitoring and control of continuous crystallization processes are highly challenging due to their nonlinear, multivariate and highly correlated nature. Present paper furnishes the successful implementation of various chemometric techniques like clustering of time series data and moving window based pattern matching aiming towards fault detection and classification of different operating conditions of a continuous crystallizer. PCA based combined similarity was chosen as the index of clustering as well as pattern matching.



Standards related to Crystallizers

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