Spatio Temporal Modeling Of Nonlinear Distributed Parameter Systems
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Spatio Temporal Modeling Of Nonlinear Distributed Parameter Systems
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Author : Han-Xiong Li
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-02-24
Spatio Temporal Modeling Of Nonlinear Distributed Parameter Systems written by Han-Xiong Li 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 2011-02-24 with Mathematics categories.
The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein systems and their identifi cation methods. Then, the traditional Volterra model is extended to DPS, which results in the spatio-temporal Volterra model and its identification algorithm. All these methods are based on linear time/space separation. Sometimes, the nonlinear time/space separation can play a better role in modeling of very complex processes. Thus, a nonlinear time/space separation based neural modeling is also presented for a class of DPS with more complicated dynamics. Finally, all these modeling approaches are successfully applied to industrial thermal processes, including a catalytic rod, a packed-bed reactor and a snap curing oven. The work is presented giving a unifi ed view from time/space separation. The book also illustrates applications to thermal processes in the electronics packaging and chemical industry. This volume assumes a basic knowledge about distributed parameter systems, system modeling and identifi cation. It is intended for researchers, graduate students and engineers interested in distributed parameter systems, nonlinear systems, and process modeling and control.
Dna Computing Based Genetic Algorithm
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Author : Jili Tao
language : en
Publisher: Springer Nature
Release Date : 2020-07-01
Dna Computing Based Genetic Algorithm written by Jili Tao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-01 with Computers categories.
This book focuses on the implementation, evaluation and application of DNA/RNA-based genetic algorithms in connection with neural network modeling, fuzzy control, the Q-learning algorithm and CNN deep learning classifier. It presents several DNA/RNA-based genetic algorithms and their modifications, which are tested using benchmarks, as well as detailed information on the implementation steps and program code. In addition to single-objective optimization, here genetic algorithms are also used to solve multi-objective optimization for neural network modeling, fuzzy control, model predictive control and PID control. In closing, new topics such as Q-learning and CNN are introduced. The book offers a valuable reference guide for researchers and designers in system modeling and control, and for senior undergraduate and graduate students at colleges and universities.
Framework For Analysis And Identification Of Nonlinear Distributed Parameter Systems Using Bayesian Uncertainty Quantification Based On Generalized Polynomial Chaos
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Author : Janya-anurak, Chettapong
language : en
Publisher: KIT Scientific Publishing
Release Date : 2017-04-04
Framework For Analysis And Identification Of Nonlinear Distributed Parameter Systems Using Bayesian Uncertainty Quantification Based On Generalized Polynomial Chaos written by Janya-anurak, Chettapong and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-04 with Electronic computers. Computer science categories.
In this work, the Uncertainty Quantification (UQ) approaches combined systematically to analyze and identify systems. The generalized Polynomial Chaos (gPC) expansion is applied to reduce the computational effort. The framework using gPC based on Bayesian UQ proposed in this work is capable of analyzing the system systematically and reducing the disagreement between the model predictions and the measurements of the real processes to fulfill user defined performance criteria.
6th International Conference On Advancements Of Medicine And Health Care Through Technology 17 20 October 2018 Cluj Napoca Romania
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Author : Simona Vlad
language : en
Publisher: Springer
Release Date : 2019-05-16
6th International Conference On Advancements Of Medicine And Health Care Through Technology 17 20 October 2018 Cluj Napoca Romania written by Simona Vlad and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-16 with Technology & Engineering categories.
This volume presents the contributions of the 6th International Conference on Advancements of Medicine and Health Care through Technology – MediTech 2018, held between 17 – 20 October 2018 in Cluj-Napoca, Romania. The papers of this Proceedings volume present new developments in : - Health Care Technology - Medical Devices, Measurement and Instrumentation - Medical Imaging, Image and Signal Processing - Modeling and Simulation - Molecular Bioengineering - Biomechanics
System Design And Control Integration For Advanced Manufacturing
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Author : Han-Xiong Li
language : en
Publisher: John Wiley & Sons
Release Date : 2014-10-27
System Design And Control Integration For Advanced Manufacturing written by Han-Xiong Li 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 2014-10-27 with Technology & Engineering categories.
Most existing robust design books address design for static systems, or achieve robust design from experimental data via the Taguchi method. Little work considers model information for robust design particularly for the dynamic system. This book covers robust design for both static and dynamic systems using the nominal model information or the hybrid model/data information, and also integrates design with control under a large operating region. This design can handle strong nonlinearity and more uncertainties from model and parameters.
Informatics In Control Automation And Robotics
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Author : Oleg Gusikhin
language : en
Publisher: Springer Nature
Release Date : 2019-10-25
Informatics In Control Automation And Robotics written by Oleg Gusikhin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-25 with Technology & Engineering categories.
The goal of this book is to familiarize readers with the latest research on, and recent advances in, the field of Informatics in Control, Automation and Robotics. It gathers a selection of papers highlighting the state-of-the-art in Intelligent Control Systems, Optimization, Robotics and Automation, Signal Processing, Sensors, Systems Modelling and Control. Combining theoretical aspects with practical applications, the book offers a well-balanced overview of the latest achievements, and will provide researchers, engineers and PhD students with both a vital update and new inspirations for their own research.
Modeling And Control Of Dynamic Spatially Distributed Systems
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Author : Yizhi Wang
language : en
Publisher: Elsevier
Release Date : 2024-11-08
Modeling And Control Of Dynamic Spatially Distributed Systems written by Yizhi Wang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-08 with Mathematics categories.
Modeling and Control of Dynamic Spatially Distributed Systems: Pharmaceutical Processes provides a balanced approach to help readers to get started quickly in the field of biochemical pharmaceuticals. From a theoretical perspective, dynamic spatially distributed systems are introduced to address their industrial applications. After identifying problems, the book provides readers with modeling and control system design techniques via a novel fuzzy set (class of objects with a continuum of grades of membership, to describe the grade of the object belonging to this fuzzy set) and intelligent computation methods.From an application perspective, the book provides a thorough understanding of Good Manufacture Practices (GMP) and the importance of identification, modelling, and intelligent control of such systems, reducing the test-and-error cost, and the R&D design time cycle of original drug development. - Provides an updated, supplemental knowledge to the body of distributed parameter systems - Covers control and analysis framework based on a state-space approach for a non-standard model from industrial complex systems - Presents a novel proposed fuzzy set and applies it to case studies to illustrate its feasibility - Includes a control system design solution from perspective of medicine production
Nonlinear System Identification
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Author : Stephen A. Billings
language : en
Publisher: John Wiley & Sons
Release Date : 2013-09-23
Nonlinear System Identification written by Stephen A. Billings 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 2013-09-23 with Technology & Engineering categories.
Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) model The orthogonal least squares algorithm that allows models to be built term by term where the error reduction ratio reveals the percentage contribution of each model term Statistical and qualitative model validation methods that can be applied to any model class Generalised frequency response functions which provide significant insight into nonlinear behaviours A completely new class of filters that can move, split, spread, and focus energy The response spectrum map and the study of sub harmonic and severely nonlinear systems Algorithms that can track rapid time variation in both linear and nonlinear systems The important class of spatio-temporal systems that evolve over both space and time Many case study examples from modelling space weather, through identification of a model of the visual processing system of fruit flies, to tracking causality in EEG data are all included to demonstrate how easily the methods can be applied in practice and to show the insight that the algorithms reveal even for complex systems NARMAX algorithms provide a fundamentally different approach to nonlinear system identification and signal processing for nonlinear systems. NARMAX methods provide models that are transparent, which can easily be analysed, and which can be used to solve real problems. This book is intended for graduates, postgraduates and researchers in the sciences and engineering, and also for users from other fields who have collected data and who wish to identify models to help to understand the dynamics of their systems.
Advances In Machine Learning Research And Application 2012 Edition
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Author :
language : en
Publisher: ScholarlyEditions
Release Date : 2012-12-26
Advances In Machine Learning Research And Application 2012 Edition written by and has been published by ScholarlyEditions this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-26 with Computers categories.
Advances in Machine Learning Research and Application / 2012 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Machine Learning. The editors have built Advances in Machine Learning Research and Application / 2012 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Machine Learning in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Advances in Machine Learning Research and Application / 2012 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
Robust Engineering Designs Of Partial Differential Systems And Their Applications
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Author : Bor-Sen Chen
language : en
Publisher: CRC Press
Release Date : 2021-12-22
Robust Engineering Designs Of Partial Differential Systems And Their Applications written by Bor-Sen Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-22 with Mathematics categories.
Most systems in science, engineering, and biology are of partial differential systems (PDSs) modeled by partial differential equations. Many books about partial differential equations have been written by mathematicians and mainly address some fundamental mathematic backgrounds and discuss some mathematic properties of partial differential equations. Only a few books on PDSs have been written by engineers; however, these books have focused mainly on the theoretical stabilization analysis of PDSs, especially mechanical systems. This book investigates both robust stabilization control design and robust filter design and reference tracking control design in mechanical, signal processing, and control systems to fill a gap in the study of PDSs. Robust Engineering Designs of Partial Differential Systems and Their Applications offers some fundamental background in the first two chapters. The rest of the chapters focus on a specific design topic with a corresponding deep investigation into robust H∞ filtering, stabilization, or tracking design for more complex and practical PDSs under stochastic fluctuation and external disturbance. This book is aimed at engineers and scientists and addresses the gap between the theoretical stabilization results of PDSs in academic and practical engineering designs more focused on the robust H∞ filtering, stabilization, and tracking control problems of linear and nonlinear PDSs under intrinsic random fluctuation and external disturbance in industrial applications. Part I provides backgrounds on PDSs, such as Galerkin’s, and finite difference methods to approximate PDSs and a fuzzy method to approximate nonlinear PDSs. Part II examines robust H∞ filter designs for the robust state estimation of linear and nonlinear stochastic PDSs. And Part III treats robust H∞ stabilization and tracking control designs of linear and nonlinear PDSs. Every chapter focuses on an engineering design topic with both theoretical design analysis and practical design examples.