Yihua Hu – författare

Motivated by the expanding role of robotics in a wide range of industrial applications, the imperative for a specialized exploration into the control dynamics of permanent magnet actuators has become apparent. These actuators are integral to contemporary robotic systems but they pose distinct challenges necessitating a dedicated exploration. The subject area encompasses a comprehensive examination of control requirements, spanning from conventional high-performance strategies to avant-garde non-position control approaches, multi-motor coordination, and fault-tolerant methodologies.The aim of the authors is to go beyond theoretical discourse by encapsulating practical applications and implementation strategies to equip researchers, engineers, and academics with a robust conceptual and practical framework for addressing the complexities characterizing permanent magnet actuator control. The comprehensive scope of this book will foster a deeper understanding and facilitate the application of advanced control strategies in the realm of robotic systems.Control of Permanent Magnet Actuators for Robotics Applications navigates the intricate intersection of robotics and control theory, focusing on permanent magnet actuators. The authors incorporate novel approaches, such as non-position control strategies and fault-tolerant design principle, special design features and real-world case studies to bridge the theoretical-practical divide. By incorporating innovative methodologies with established theories, the book offers a nuanced perspective on contemporary challenges and solutions in the realm of robotic control systems.Written for an audience of robotics and mechatronics engineers, control system designers, researchers and scientists working on robotics and control theory, and advanced students of robotics, mechatronics, control and automation, this book offers readers a systematic and thorough review of permanent magnet actuators and their control for robotics applications.

The motor drive system plays a significant role in the safety and function of electric vehicles as a bridge for power transmission. In order to enhance the efficiency and stability of the drive system, more and more studies based on AI technology are devoted to the fault detection and diagnosis of the motor drive system.AI Techniques in EV Motor and Inverter Fault Detection and Diagnosis comprehensively covers the recently-developed AI applications for solving condition monitoring and fault detection issues in EV electrical conversion systems. AI-based fault detection and diagnosis (FDD) is divided into two main steps: feature extraction and fault classification. The application of different signal processing methods in feature extraction is discussed. In particular, the application of traditional machine learning and deep learning algorithms for fault classification is presented in detail. In addition, the characteristics of all techniques reviewed are summarised.Chapters systematically address condition monitoring and fault detection in EV motors and inverters. Four case studies are including, covering AI based electric motor fault diagnosis, AI based inverter/IGBT fault diagnosis, AI based bearing fault diagnosis, and AI based gearbox fault diagnosis. Alongside each case study, the authors discuss the differences between conventional methods and AI-based methods in EV applications, and the motivation, advantages, shortcomings and challenges of AI-based methods. Finally, the latest developments, research gaps and future challenges in fault monitoring and diagnosis of motor faults are explored.Providing a systematic and thorough exploration of its field, this book is a valuable resource for researchers and students with an interest in the applications of AI in electric vehicles, and for engineers and research and development professionals in the electric automotive industry.

The book offers an invaluable resource for researchers, especially those who are engaged in the fields including target detection based on a laser imaging system, target detection and identification, remote sensing imaging and image processing.

The book offers an invaluable resource for researchers, especially those who are engaged in the fields including target detection based on a laser imaging system, target detection and identification, remote sensing imaging and image processing.

This book highlights the novel photoelectric detection technique on derived attributes of targets. It is achieved by acquiring three types of attributes of the target, including those that reflect the essential features of parts of the target, those directly generated from the target, and those synthesized by the target features.

This book highlights the novel photoelectric detection technique on derived attributes of targets. Photoelectric detection on derived attributes of targets is a new target detection and monitoring method. It is achieved by acquiring three types of attributes of the target, including those that reflect the essential features of parts of the target, those directly generated from the target, and those synthesized by the target features. The book introduces the classification of derived attributes of targets and describes typical detection methods. Emphases are put on laser detection of aerial moving targets, using derived attributes such as the disturbance of atmospheric wind fields, trailing vortexes, and the disturbance of atmospheric components. The authors also elaborate on visible light imaging detection using derived attributes such as retroreflection and the identification of target carriers. Besides, the synthetic attributes processing of integrated aerospace images is introducedfor the detection of targets on the ground and sea surfaces. This book can be used as a good reference for researchers engaged in the fields of photoelectric detection, target detection and image processing, and as a reference book for senior undergraduates and postgraduates in relevant majors.