Jing Xu – författare

This book is a self-contained collection of recent research findings providing a comprehensive and systematic unified framework for both analysis and synthesis for singularly perturbed systems. It paves the way for the gap between frequency-domain-transfer-function-based results and time-domain-state-space-based results to be bridged.

It is divided into three parts focusing on: fundamental background of singular perturbation; general singular perturbation methodologies and time-scale techniques and the theoretical foundation of finite-frequency control; the analysis and synthesis of singularly perturbed systems; and real-world engineering applications implementing the results developed in systems like wind turbines and autonomous-aerial-vehicle hovering.

This book focuses on key simulation and evaluation technologies for 5G systems. Based on the most recent research results from academia and industry, it describes the evaluation methodologies in depth for network and physical layer technologies. The evaluation methods are discussed in depth. It also covers the analysis of the 5G candidate technologies and the testing challenges, the evolution of the testing technologies, fading channel measurement and modeling, software simulations, software hardware cosimulation, field testing and other novel evaluation methods. The fifth-generation (5G) mobile communications system targets highly improved network performances in terms of the network capacity and the number of connections.

Students focused on telecommunications, electronic engineering, computer science or other related disciplines will find this book useful as a secondary text. Researchers and professionals working within these related fields will also find this book useful as a reference.

This book explores peg-in-hole assembly strategies to study robotic intelligent assembly. It presents several state-of-the-art principles for peg-in-hole assembly strategies, supported by experimental evidence. In pursuit of theoretical innovation, the author summarizes their research on robotic intelligent assembly over the past decade, highlighting the limitations of model-based algorithms in complex assembly environments and the importance of data efficiency for learning-based algorithms. Each algorithm is supported by extensive experimentation and results demonstrating its effectiveness. A review of research ideas provides readers with a comprehensive understanding of the progress made in this field. This monograph is intended for undergraduate and postgraduate students interested in robotic intelligent assembly, researchers studying robotic intelligent assembly algorithms, and electronic, mechanical, and computer engineers engaged in industrial robot-assisted assembly.