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Surveys and Tutorials in the Applied Mathematical Sciences

Orosz G: Dynamics and Control of
Connected Vehicles

Dynamics and Control of Connected Vehicles

Mathematical Phyllotaxis

Mechanics is one of the oldest and most foundational subjects in undergraduate curricula for mathematicians, physicists, and engineers. Traditionally taught through a classical, or "analytical," approach, modern advancements have introduced a "geometric" perspective that has found applications in diverse fields such as machine learning, climate research, satellite navigation, and more.

This book bridges the gap between classical mechanics and its modern, geometric counterpart. Designed for students and educators, it presents the essential topics typically required in mechanics courses while integrating a geometric approach to deepen understanding.

Key features include:

*Clear explanations of core concepts, including Lagrangian mechanics, variational methods, canonical transformations, and systems with constraints.

*Numerous solved problems and real-world examples to solidify understanding.

*Sample midterms and final exams to help students prepare for coursework and assessments.

*Every chapter includes a 'looking forward' section outlining modern applications of the material

The book minimizes mathematical abstraction, introducing only the necessary concepts to make the material accessible and practical. Whether you're a student looking to master the essentials or an instructor seeking a fresh perspective, this book provides a comprehensive, approachable, and modern exploration of mechanics.

Mechanics is one of the oldest and most foundational subjects in undergraduate curricula for mathematicians, physicists, and engineers. Traditionally taught through a classical, or "analytical," approach, modern advancements have introduced a "geometric" perspective that has found applications in diverse fields such as machine learning, climate research, satellite navigation, and more.This book bridges the gap between classical mechanics and its modern, geometric counterpart. Designed for students and educators, it presents the essential topics typically required in mechanics courses while integrating a geometric approach to deepen understanding.Key features include:*Clear explanations of core concepts, including Lagrangian mechanics, variational methods, canonical transformations, and systems with constraints.*Numerous solved problems and real-world examples to solidify understanding.*Sample midterms and final exams to help students prepare for coursework and assessments.*Every chapter includes a ‘looking forward’ section outlining modern applications of the material.The book minimizes mathematical abstraction, introducing only the necessary concepts to make the material accessible and practical. Whether you're a student looking to master the essentials or an instructor seeking a fresh perspective, this book provides a comprehensive, approachable, and modern exploration of mechanics.

A Concise Introduction to Classical Mechanics

Communications and Control Engineering

Nonlinear Networked Systems and Control

Springer Optimization and Its Applications

OTSE Conference Proceedings, 13‒15 December 2023, L'Aquila (Italy)

New Trends and Challenges in Optimization Theory Applied to Space Engineering

SpringerBriefs in Mathematics

This book provides an introduction to the theory of connection matrices in the context of combinatorial multivector fields. The theory of connection matrices was proposed by Conley and Franzosa for classical continuous-time dynamical systems as a tool for studying connecting orbits between isolated invariant sets. It generalizes the Morse complex in Morse theory, and has found numerous applications in dynamics. Connection matrices have been and still are a challenging topic to study, as there are no complete introductory texts, and both their intricate definition and properties are scattered over numerous research papers.
In recent years, dynamical concepts have found their way into a combinatorial context. Starting with combinatorial vector fields, introduced by Forman to generalize classical Morse theory, it has been realized that this transfer of ideas can lead to important applications. Similarly, Conley's theory of isolated invariant sets has been transferred to the combinatorial setting. This, when combined with the concept of multivector fields, opens the door to a complete combinatorial dynamical theory.
In this book, we take Conley's theory one step further, by presenting a complete discussion of connection matrices for combinatorial multivector fields. While some of the results in this book are based on known approaches, we show in a detailed way how they can be carried over to the case of multivector fields on general Lefschetz complexes. Along the way, we introduce notions which are new even in the classical setting, such as a formal approach to addressing the nonuniqueness of connection matrices, as well as mechanisms for comparing connection matrices even under poset changes. Finally, we show that specifically for the case of Forman's gradient combinatorial vector fields connection matrices are necessarily unique, and can be determined explicitly in a straightforward way.
Focusing on the combinatorial theory of connection matrices has a number of advantages. On the one hand, many of the technical difficulties of the classical continuous-time dynamics situation are not present in the discrete combinatorial context. This allows us to provide a complete and informal introduction to the theory in the second section of the book. This in turn will enable the readers to construct and analyze their own examples easily. On the other hand, the complete theory, including the existence of connecting orbits in the combinatorial setting can be presented in detail, based on an explicit distinction between the algebraic and topological parts of the theory. In this way, it is our hope that this book will be an impetus for further knowledge transfer between dynamics and combinatorics, and even topological data analysis.
This text is aimed at researchers in the fields of dynamics and topological data analysis, and it is suitable for advanced graduate students interested in applying connection matrix methods to their own studies.

Connection Matrices in Combinatorial Topological Dynamics

Dynamical Systems with Applications using MATLAB®

Advances in Industrial Control

This book introduces an optimal iterative learning control (ILC) design framework from the end user's point of view. Its central theme is the understanding of model dynamics, the construction of a procedure for systematic input updating and their contribution to successful algorithm design. The authors discuss the many applications of ILC in industrial systems, applications such as robotics and mechanical testing.The text covers a number of optimal ILC design methods, including gradient-based and norm-optimal ILC. Their convergence properties are described and detailed design guidelines, including performance-improvement mechanisms, are presented. Readers are given a clear picture of the nature of ILC and the benefits of the optimization-based approach from the conceptual and mathematical foundations of the problem of algorithm construction to the impact of available parameters in making acceleration of algorithmic convergence possible. Three case studies on robotic platforms, an electro-mechanical machine, and robot-assisted stroke rehabilitation are included to demonstrate the application of these methods in the real-world.&nbsp;With its emphasis on basic concepts, detailed design guidelines and examples of benefits,&nbsp;Optimal Iterative Learning Control&nbsp;will be of value to practising engineers and academic researchers alike.

A Practitioner's Guide

Optimal Iterative Learning Control

Communications in Computer and Information Science

This book constitutes the refereed proceedings of the First International Symposium on Intelligent Technology for Future Transportation, ITFT 2024, held in Helsinki, Finland, during October 19-21, 2024.


The 32 full papers presented in this volume were carefully reviewed and selected from 74 submissions. They are organized according to the following topics: Intelligent Vehicle Technology and Applications; Intelligent Transportation Management and Traffic Flow Analysis; and Intelligent Transportation Infrastructure and Sustainable Transportation.

This book constitutes the refereed proceedings of the First International Symposium on Intelligent Technology for Future Transportation, ITFT 2024, held in Helsinki, Finland, during October 19–21, 2024.The 32 full papers presented in this volume were carefully reviewed and selected from 74 submissions. They are organized according to the following topics:Intelligent Vehicle Technology and Applications;&nbsp;Intelligent Transportation Management and Traffic Flow Analysis; and Intelligent Transportation Infrastructure and Sustainable Transportation.

First International Symposium, ITFT 2024, Helsinki, Finland, October 19–21, 2024, Proceedings

Intelligent Technology for Future Transportation

Lecture Notes in Control and Information Sciences

This monograph concentrates on the theory of robust control of linear impulsive stochastic systems and stochastic systems with jumps. It discusses theoretical points concerned with impulsive stochastic systems including optimal control, robust stabilization, and H2- and Hinfinity-type results. Considering the major role played by the impulsive Lyapunov and impulsive Riccati equations in these problems, the book presents a thorough treatment of these equations in a general framework. It also presents various applications to sampled-data control.Robust Control of Jump Linear Stochastic Systems is a self-contained and clearly structured presentation of up-to-date research in this area, relevant to researchers in control theory and to non-specialists who are interested in the theory of robust control of linear impulsive stochastic systems. Theoretical and applied mathematicians, research engineers, and graduate students in the aforementioned fields will also find value in this book.

Applications to Sampled-Data Control

Robust Control of Jump Linear Stochastic Systems

Wireless Networks

This book delves into the problems and challenges faced in achieving improved performance in connected vehicles traffic flow prediction in intelligent connected transportation systems and provides an in-depth analysis of spatial-temporal feature extraction, global local spatial feature extraction, and fusion of external factors. The book is divided into ten chapters, and the introductory section presents the history of the development of artificial intelligence and graph neural networks in the context of connected vehicles, related work on prediction of connected traffic, and preliminary knowledge. Chapter 2 to 9 present eight prediction methods in the context of connected traffic, respectively. Each section includes an introduction to the problem definition, model architecture, experimental setup, and discussion of results, as well as references. The last section summarizes the contributions of the book and future challenges.

<ul>
	<li>Covers performance in connected vehicles traffic flow prediction in intelligent connected transportation systems;</li>
	<li>Presents connected traffic flow prediction solutions that ensure model performance;</li>
	<li>Proposes solutions demonstrated with proof-of-concept prototype implementations, written in open-source Python.</li>
</ul>

Emerging GNN Methods

Connected Vehicles Traffic Prediction

Fundamentals of Turbulence and its Modeling

This book presents the theoretical foundations of the comparison approach and demonstrates how this method can be used for the development of techniques for the analysis and design of control systems in the state-space domain. It provides a framework for using the comparison approach to solve fundamental analysis and design problems of control systems, including invariance and contractivity, stability analysis and constrained control.Within this framework, the book shows the reader that the invariance of sets represented by sublevel subsets, the control-invariant regions, the stability properties and the design of constrained controllers for both continuous-time and discrete-time systems can be investigated using comparison systems. The dual approach of analysis and design, based on the representation of state-space regions in terms of a number of generators and a generating function, is developed. Polyhedral invariant sets, polyhedral control invariance, stability analysis using polyhedral Lyapunov functions and constrained control under linear constraints are also investigated.Comparison Methods in Control begins with an introduction and discusses stability, Lyapunov theory, and representation of connected sets. The book progresses through comparison in different contexts, such as comparison and invariance, comparison and stability, dual comparison systems and control invariance. Constrained regulation problems and constrained control of disturbed and parameter uncertain systems are all given equal attention. Researchers and postgraduate students with backgrounds in systems analysis, control and applied mathematics will find this monograph of interest.

Comparison Methods in Control

Control Systems Benchmarks

Space Technology Library

Spacecraft Momentum Control Systems

Dynamics and Control of Connected Vehicles

Bibliografische Angaben

Schlagworte

Bibliografische Angaben

Schlagworte

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