Nonlinear Predictive Control Using Wiener Models
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Nonlinear Predictive Control Using Wiener Models
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Author : Maciej Ławryńczuk
language : en
Publisher: Springer Nature
Release Date : 2021-09-21
Nonlinear Predictive Control Using Wiener Models written by Maciej Ławryńczuk and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-21 with Technology & Engineering categories.
This book presents computationally efficient MPC solutions. The classical model predictive control (MPC) approach to control dynamical systems described by the Wiener model uses an inverse static block to cancel the influence of process nonlinearity. Unfortunately, the model's structure is limited, and it gives poor control quality in the case of an imperfect model and disturbances. An alternative is to use the computationally demanding MPC scheme with on-line nonlinear optimisation repeated at each sampling instant. A linear approximation of the Wiener model or the predicted trajectory is found on-line. As a result, quadratic optimisation tasks are obtained. Furthermore, parameterisation using Laguerre functions is possible to reduce the number of decision variables. Simulation results for ten benchmark processes show that the discussed MPC algorithms lead to excellent control quality. For a neutralisation reactor and a fuel cell, essential advantages of neural Wiener models are demonstrated.
Integrated Process Modeling Advanced Control And Data Analytics For Optimizing Polyolefin Manufacturing
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Author : Y. A. Liu
language : en
Publisher: John Wiley & Sons
Release Date : 2023-07-25
Integrated Process Modeling Advanced Control And Data Analytics For Optimizing Polyolefin Manufacturing written by Y. A. Liu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-25 with Technology & Engineering categories.
Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing Detailed resource on the “Why,” “What,” and “How” of integrated process modeling, advanced control and data analytics explained via hands-on examples and workshops for optimizing polyolefin manufacturing. Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing discusses, as well as demonstrates, the optimization of polyolefin production by covering topics from polymer process modeling and advanced process control to data analytics and machine learning, and sustainable design and industrial practice. The text also covers practical problems, handling of real data streams, developing the right level of detail, and tuning models to the available data, among other topics, to allow for easy translation of concepts into practice. Written by two highly qualified authors, Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing includes information on: Segment-based modeling of polymer processes; selection of thermodynamic methods; estimation of physical properties for polymer process modeling Reactor modeling, convergence tips and data-fit tool; free radical polymerization (LDPE, EVA and PS), Ziegler-Natta polymerization (HDPE, PP, LLPDE, and EPDM) and ionic polymerization (SBS rubber) Improved polymer process operability and control through steady-state and dynamic simulation models Model-predictive control of polyolefin processes and applications of multivariate statistics and machine learning to optimizing polyolefin manufacturing Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing enables readers to make full use of advanced computer models and latest data analytics and machine learning tools for optimizing polyolefin manufacturing, making it an essential resource for undergraduate and graduate students, researchers, and new and experienced engineers involved in the polyolefin industry.
Electronics And Signal Processing
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Author : Wensong Hu
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-21
Electronics And Signal Processing written by Wensong Hu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-21 with Technology & Engineering categories.
This volume includes extended and revised versions of a set of selected papers from the International Conference on Electric and Electronics (EEIC 2011) , held on June 20-22 , 2011, which is jointly organized by Nanchang University, Springer, and IEEE IAS Nanchang Chapter. The objective of EEIC 2011 Volume 1 is to provide a major interdisciplinary forum for the presentation of new approaches from Electronics and Signal Processing, to foster integration of the latest developments in scientific research. 133 related topic papers were selected into this volume. All the papers were reviewed by 2 program committee members and selected by the volume editor Prof. Wensong Hu. We hope every participant can have a good opportunity to exchange their research ideas and results and to discuss the state of the art in the areas of the Electronics and Signal Processing.
Foundations Of Intelligent Systems
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Author : Marzena Kryszkiewics
language : en
Publisher: Springer
Release Date : 2011-06-24
Foundations Of Intelligent Systems written by Marzena Kryszkiewics and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-24 with Computers categories.
This book constitutes the refereed proceedings of the 19th International Symposium on Methodologies for Intelligent Systems, ISMIS 2011, held in Warsaw, Poland, in June 2011. The 71 revised papers presented together with 3 invited papers were carefully reviewed and selected from 131 submissions. The papers are organized in topical sections on rough sets - in memoriam Zdzisław Pawlik, challenges in knowledge discovery and data mining - in memoriam Jan Żytkov, social networks, multi-agent systems, theoretical backgrounds of AI, machine learning, data mining, mining in databases and warehouses, text mining, theoretical issues and applications of intelligent web, application of intelligent systems in sound processing, intelligent applications in biology and medicine, fuzzy sets theory and applications, intelligent systems, tools and applications, and contest on music information retrieval.
Advanced Model Predictive Control
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Author : Tao Zheng
language : en
Publisher: BoD – Books on Demand
Release Date : 2011-07-05
Advanced Model Predictive Control written by Tao Zheng and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-05 with Technology & Engineering categories.
Model Predictive Control (MPC) refers to a class of control algorithms in which a dynamic process model is used to predict and optimize process performance. From lower request of modeling accuracy and robustness to complicated process plants, MPC has been widely accepted in many practical fields. As the guide for researchers and engineers all over the world concerned with the latest developments of MPC, the purpose of "Advanced Model Predictive Control" is to show the readers the recent achievements in this area. The first part of this exciting book will help you comprehend the frontiers in theoretical research of MPC, such as Fast MPC, Nonlinear MPC, Distributed MPC, Multi-Dimensional MPC and Fuzzy-Neural MPC. In the second part, several excellent applications of MPC in modern industry are proposed and efficient commercial software for MPC is introduced. Because of its special industrial origin, we believe that MPC will remain energetic in the future.
Adaptive And Natural Computing Algorithms
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Author : Andrej Dobnikar
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-03-03
Adaptive And Natural Computing Algorithms written by Andrej Dobnikar and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-03 with Computers categories.
The two-volume set LNCS 6593 and 6594 constitutes the refereed proceedings of the 10th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2010, held in Ljubljana, Slovenia, in April 2010. The 83 revised full papers presented were carefully reviewed and selected from a total of 144 submissions. The first volume includes 42 papers and a plenary lecture and is organized in topical sections on neural networks and evolutionary computation.
Computationally Efficient Model Predictive Control Algorithms
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Author : Maciej Ławryńczuk
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-01-24
Computationally Efficient Model Predictive Control Algorithms written by Maciej Ławryńczuk and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-24 with Technology & Engineering categories.
This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: · A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. · Implementation details of the MPC algorithms for feed forward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. · The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). · The MPC algorithms with neural approximation with no on-line linearization. · The MPC algorithms with guaranteed stability and robustness. · Cooperation between the MPC algorithms and set-point optimization. Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require demanding on-line nonlinear optimization. The presented simulation results demonstrate high accuracy and computational efficiency of the algorithms. For a few representative nonlinear benchmark processes, such as chemical reactors and a distillation column, for which the classical MPC algorithms based on linear models do not work properly, the trajectories obtained in the suboptimal MPC algorithms are very similar to those given by the ``ideal'' MPC algorithm with on-line nonlinear optimization repeated at each sampling instant. At the same time, the suboptimal MPC algorithms are significantly less computationally demanding.
Modeling And Control In Air Conditioning Systems
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Author : Ye Yao
language : en
Publisher: Springer
Release Date : 2016-10-01
Modeling And Control In Air Conditioning Systems written by Ye Yao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-01 with Technology & Engineering categories.
This book investigates the latest modeling and control technologies in the context of air-conditioning systems. Firstly, it introduces the state-space method for developing dynamic models of all components in a central air-conditioning system. The models are primarily nonlinear and based on the fundamental principle of energy and mass conservation, and are transformed into state-space form through linearization. The book goes on to describe and discuss the state-space models with the help of graph theory and the structure-matrix theory. Subsequently, virtual sensor calibration and virtual sensing methods (which are very useful for real system control) are illustrated together with a case study. Model-based predictive control and state-space feedback control are applied to air-conditioning systems to yield better local control, while the air-side synergic control scheme and a global optimization strategy based on the decomposition-coordination method are developed so as to achieve energy conservation in the central air-conditioning system. Lastly, control strategies for VAV systems including total air volume control and trim & response static pressure control are investigated in practice.
Automatic Control Robotics And Information Processing
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Author : Piotr Kulczycki
language : en
Publisher: Springer Nature
Release Date : 2020-09-03
Automatic Control Robotics And Information Processing written by Piotr Kulczycki and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-03 with Technology & Engineering categories.
This book presents a wide and comprehensive range of issues and problems in various fields of science and engineering, from both theoretical and applied perspectives. The desire to develop more effective and efficient tools and techniques for dealing with complex processes and systems has been a natural inspiration for the emergence of numerous fields of science and technology, in particular control and automation and, more recently, robotics. The contributions gathered here concern the development of methods and algorithms to determine best practices regarding broadly perceived decisions or controls. From an engineering standpoint, many of them focus on how to automate a specific process or complex system. From a tools-based perspective, several contributions address the development of analytic and algorithmic methods and techniques, devices and systems that make it possible to develop and subsequently implement the automation and robotization of crucial areas of human activity. All topics discussed are illustrated with sample applications.
Model Predictive Control
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Author : Carlos Bordons Alba
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Model Predictive Control written by Carlos Bordons Alba and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
In recent years Model Predictive Control (MPC) schemes have established themselves as the preferred control strategy for a large number of processes. Their ability to handle constraints and multivariable processes and their intuitive way of posing the pro cess control problem in the time domain are two reasons for their popularity. This volume by authors of international repute provides an extensive review concerning the theoretical and practical aspects of predictive controllers. It describes the most commonly used MPC strategies, especially Generalised Predictive Control (GPC), showing both their theoretical properties and their practical implementation issues. Topics such as multivariable MPC, constraint handling, stability and robustness properties are thoroughly analysed in this text.