Automating Data Driven Modelling Of Dynamical Systems PDF Download
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| Author | : Dhruv Khandelwal |
| Publisher | : Springer Nature |
| Total Pages | : 250 |
| Release | : 2022-02-03 |
| Genre | : Technology & Engineering |
| ISBN | : 3030903435 |
Download Automating Data-Driven Modelling of Dynamical Systems Book in PDF, ePub and Kindle
This book describes a user-friendly, evolutionary algorithms-based framework for estimating data-driven models for a wide class of dynamical systems, including linear and nonlinear ones. The methodology addresses the problem of automating the process of estimating data-driven models from a user’s perspective. By combining elementary building blocks, it learns the dynamic relations governing the system from data, giving model estimates with various trade-offs, e.g. between complexity and accuracy. The evaluation of the method on a set of academic, benchmark and real-word problems is reported in detail. Overall, the book offers a state-of-the-art review on the problem of nonlinear model estimation and automated model selection for dynamical systems, reporting on a significant scientific advance that will pave the way to increasing automation in system identification.
| Author | : Steven L. Brunton |
| Publisher | : Cambridge University Press |
| Total Pages | : 615 |
| Release | : 2022-05-05 |
| Genre | : Computers |
| ISBN | : 1009098489 |
Download Data-Driven Science and Engineering Book in PDF, ePub and Kindle
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
| Author | : J. Nathan Kutz |
| Publisher | : SIAM |
| Total Pages | : 241 |
| Release | : 2016-11-23 |
| Genre | : Science |
| ISBN | : 1611974496 |
Download Dynamic Mode Decomposition Book in PDF, ePub and Kindle
Data-driven dynamical systems is a burgeoning field?it connects how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific fields are not typically known. Thus, using data alone to help derive, in an optimal sense, the best dynamical system representation of a given application allows for important new insights. The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections with traditional dynamical systems theory and many recent innovations in compressed sensing and machine learning. Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, the first book to address the DMD algorithm, presents a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development; blends theoretical development, example codes, and applications to showcase the theory and its many innovations and uses; highlights the numerous innovations around the DMD algorithm and demonstrates its efficacy using example problems from engineering and the physical and biological sciences; and provides extensive MATLAB code, data for intuitive examples of key methods, and graphical presentations.
| Author | : J. Nathan Kutz |
| Publisher | : Oxford University Press |
| Total Pages | : 657 |
| Release | : 2013-08-08 |
| Genre | : Computers |
| ISBN | : 0199660336 |
Download Data-Driven Modeling & Scientific Computation Book in PDF, ePub and Kindle
Combining scientific computing methods and algorithms with modern data analysis techniques, including basic applications of compressive sensing and machine learning, this book develops techniques that allow for the integration of the dynamics of complex systems and big data. MATLAB is used throughout for mathematical solution strategies.
| Author | : Radu-Emil Precup |
| Publisher | : CRC Press |
| Total Pages | : 408 |
| Release | : 2021-12-27 |
| Genre | : Technology & Engineering |
| ISBN | : 1000519635 |
Download Data-Driven Model-Free Controllers Book in PDF, ePub and Kindle
This book categorizes the wide area of data-driven model-free controllers, reveals the exact benefits of such controllers, gives the in-depth theory and mathematical proofs behind them, and finally discusses their applications. Each chapter includes a section for presenting the theory and mathematical definitions of one of the above mentioned algorithms. The second section of each chapter is dedicated to the examples and applications of the corresponding control algorithms in practical engineering problems. This book proposes to avoid complex mathematical equations, being generic as it includes several types of data-driven model-free controllers, such as Iterative Feedback Tuning controllers, Model-Free Controllers (intelligent PID controllers), Model-Free Adaptive Controllers, model-free sliding mode controllers, hybrid model‐free and model‐free adaptive‐Virtual Reference Feedback Tuning controllers, hybrid model-free and model-free adaptive fuzzy controllers and cooperative model-free controllers. The book includes the topic of optimal model-free controllers, as well. The optimal tuning of model-free controllers is treated in the chapters that deal with Iterative Feedback Tuning and Virtual Reference Feedback Tuning. Moreover, the extension of some model-free control algorithms to the consensus and formation-tracking problem of multi-agent dynamic systems is provided. This book can be considered as a textbook for undergraduate and postgraduate students, as well as a professional reference for industrial and academic researchers, attracting the readers from both industry and academia.
| Author | : Étienne André |
| Publisher | : Springer Nature |
| Total Pages | : 339 |
| Release | : 2023-10-18 |
| Genre | : Computers |
| ISBN | : 3031453328 |
Download Automated Technology for Verification and Analysis Book in PDF, ePub and Kindle
This book constitutes the refereed proceedings of the 21st International Symposium on Automated Technology for Verification and Analysis, ATVA 2023, held in Singapore, in October 2023. The symposium intends to promote research in theoretical and practical aspects of automated analysis, verification and synthesis by providing a forum for interaction between regional and international research communities and industry in related areas. The 30 regular papers presented together with 7 tool papers were carefully reviewed and selected from 150 submissions.The papers are divided into the following topical sub-headings: Temporal logics, Data structures and heuristics, Verification of programs and hardware.
| Author | : Anand Kumar M |
| Publisher | : Springer Nature |
| Total Pages | : 362 |
| Release | : 2023-05-28 |
| Genre | : Computers |
| ISBN | : 3031332318 |
Download Speech and Language Technologies for Low-Resource Languages Book in PDF, ePub and Kindle
This book constitutes refereed proceedings from the First International Conference on Speech and Language Technologies for Low-resource Languages, SPELLL 2022, held in Kalavakkam, India, in November 2022. The 25 presented papers were thoroughly reviewed and selected from 70 submissions. The papers are organised in the following topical sections: language resources; language technologies; speech technologies; multimodal data analysis; fake news detection in low-resource languages (regional-fake); low resource cross-domain, cross-lingualand cross-modal offensie content analysis (LC4).
| Author | : Bela G. Liptak |
| Publisher | : CRC Press |
| Total Pages | : 3560 |
| Release | : 2022-08-31 |
| Genre | : Technology & Engineering |
| ISBN | : 1000820629 |
Download Instrument and Automation Engineers' Handbook Book in PDF, ePub and Kindle
The Instrument and Automation Engineers’ Handbook (IAEH) is the Number 1 process automation handbook in the world. The two volumes in this greatly expanded Fifth Edition deal with measurement devices and analyzers. Volume one, Measurement and Safety, covers safety sensors and the detectors of physical properties, while volume two, Analysis and Analysis, describes the measurement of such analytical properties as composition. Complete with 245 alphabetized chapters and a thorough index for quick access to specific information, the IAEH, Fifth Edition is a must-have reference for instrument and automation engineers working in the chemical, oil/gas, pharmaceutical, pollution, energy, plastics, paper, wastewater, food, etc. industries.
| Author | : Wang Jianhong |
| Publisher | : CRC Press |
| Total Pages | : 363 |
| Release | : 2023-03-31 |
| Genre | : Computers |
| ISBN | : 1000860272 |
Download Data Driven Strategies Book in PDF, ePub and Kindle
A key challenge in science and engineering is to provide a quantitative description of the systems under investigation, leveraging the noisy data collected. Such a description may be a complete mathematical model or a mechanism to return controllers corresponding to new, unseen inputs. Recent advances in the theories are described in detail, along with their applications in engineering. The book aims to develop model-free system analysis and control strategies, i.e., data-driven control from theoretical analysis and engineering applications based only on measured data. The study aims to develop system identification, and combination in advanced control theory, i.e., data-driven control strategy as system and controller are generated from measured data directly. The book reviews the development of system identification and its combination in advanced control theory, i.e., data-driven control strategy, as they all depend on measured data. Firstly, data-driven identification is developed for the closed-loop, nonlinear system and model validation, i.e., obtaining model descriptions from measured data. Secondly, the data-driven idea is combined with some control strategies to be considered data-driven control strategies, such as data-driven model predictive control, data-driven iterative tuning control, and data-driven subspace predictive control. Thirdly data-driven identification and data-driven control strategies are applied to interested engineering. In this context, the book provides algorithms to perform state estimation of dynamical systems from noisy data and some convex optimization algorithms through identification and control problems.
| Author | : Peter Benner |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 346 |
| Release | : 2021-11-08 |
| Genre | : Mathematics |
| ISBN | : 3110497719 |
Download System- and Data-Driven Methods and Algorithms Book in PDF, ePub and Kindle
An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This first volume focuses on real-time control theory, data assimilation, real-time visualization, high-dimensional state spaces and interaction of different reduction techniques.
