Data-Driven Spatiotemporal Modeling and Control of Nonlinear Distributed Parameter Systems and Their Applications | 25.2 MB
Title: Data-Driven Spatiotemporal Modeling and Control of Nonlinear Distributed Parameter Systems and Their Applications
Author: Dong Shen
Category: Nonfiction, Science & Nature, Science, Other Sciences, System Theory, Technology, Electricity, Engineering
Language: English | 292 Pages | ISBN: 981954114X
Description:
This book provides a systematic overview and classification on modeling and control of different types of Distributed Parameter Systems (DPSs), and develops new methods to tackle some of these unsolved problems, facilitating a better understanding of DPSs and providing references for practical problem-solving in the relevant fields. All these methods presented in this book are verified by specific scenarios. It is worth mentioning that in the context of disciplinary integration and artificial intelligence, the research ideas, methods and models in this book can be further integrated and developed. From application perspectives, they can also extend from traditional mechanical, electrical, and chemical fields to emerging fields of new energy, new materials, and multimodal information. Under the background of disciplinary integration and the development of artificial intelligence, the book will be beneficial to undergraduate and postgraduate students in interdisciplinary disciplines including manufacturing engineering, mechanical engineering, electrical engineering, computer engineering, and control engineering, etc. It is also intended for researchers and practical users in the fields of nonlinear dynamics, spatiotemporal modeling and intelligent control.
This book provides a systematic overview and classification on modeling and control of different types of Distributed Parameter Systems (DPSs), and develops new methods to tackle some of these unsolved problems, facilitating a better understanding of DPSs and providing references for practical problem-solving in the relevant fields. All these methods presented in this book are verified by specific scenarios. It is worth mentioning that in the context of disciplinary integration and artificial intelligence, the research ideas, methods and models in this book can be further integrated and developed. From application perspectives, they can also extend from traditional mechanical, electrical, and chemical fields to emerging fields of new energy, new materials, and multimodal information. Under the background of disciplinary integration and the development of artificial intelligence, the book will be beneficial to undergraduate and postgraduate students in interdisciplinary disciplines including manufacturing engineering, mechanical engineering, electrical engineering, computer engineering, and control engineering, etc. It is also intended for researchers and practical users in the fields of nonlinear dynamics, spatiotemporal modeling and intelligent control.
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