Sensor Fusion for Nanopositioning


Book Description

Master's Thesis from the year 2014 in the subject Electrotechnology, grade: 2, Vienna University of Technology (Institute for Automation & Control), course: Master in Automation - Electrical Enginnering, language: English, abstract: Sensors can be used to measure the position of an object. In the present thesis the effects which limit the usage of sensors in high dynamic positioning applications on a nanometer level are discussed. Various sensor principles and their properties are investigated and compared. Sensors based on the measurement of i.a. magnetic fields, illumination, or even strain are characterized, as well as their range, bandwidth, resolution, linearity and disturbance rejection is determined. It will be shown that the simultaneous use of multiple sensors and the specific combination of sensors’ data (fusion) enables a higher performance primarily in terms of resolution and dynamics. Several techniques for the fusion are discussed under consideration of various aspects, however the ultimate aim of sensor fusion is similar. The methods of feedforward control, complementary filtering, Kalman filtering and optimal filtering (robust control) are developed and verified on practical problems in position sensor systems. To treat various challenges in sensor filtering and sensor fusion a methodological approach, containing separable steps of • problem formulation with well-defined prerequisits and simplifications, • theory discussion with approach to find a solution, • analytical proof or reasoning by statistical values out of numerical simulations, • experiment design, and • verification on a real time platform are realized.




Design, Modeling and Control of Nanopositioning Systems


Book Description

Covering the complete design cycle of nanopositioning systems, this is the first comprehensive text on the topic. The book first introduces concepts associated with nanopositioning stages and outlines their application in such tasks as scanning probe microscopy, nanofabrication, data storage, cell surgery and precision optics. Piezoelectric transducers, employed ubiquitously in nanopositioning applications are then discussed in detail including practical considerations and constraints on transducer response. The reader is then given an overview of the types of nanopositioner before the text turns to the in-depth coverage of mechanical design including flexures, materials, manufacturing techniques, and electronics. This process is illustrated by the example of a high-speed serial-kinematic nanopositioner. Position sensors are then catalogued and described and the text then focuses on control. Several forms of control are treated: shunt control, feedback control, force feedback control and feedforward control (including an appreciation of iterative learning control). Performance issues are given importance as are problems limiting that performance such as hysteresis and noise which arise in the treatment of control and are then given chapter-length attention in their own right. The reader also learns about cost functions and other issues involved in command shaping, charge drives and electrical considerations. All concepts are demonstrated experimentally including by direct application to atomic force microscope imaging. Design, Modeling and Control of Nanopositioning Systems will be of interest to researchers in mechatronics generally and in control applied to atomic force microscopy and other nanopositioning applications. Microscope developers and mechanical designers of nanopositioning devices will find the text essential reading.







Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System


Book Description

This book includes selected papers from the 13th IEEE International Conference on Multisensor Integration and Fusion for Intelligent Systems (MFI 2017) held in Daegu, Korea, November 16–22, 2017. It covers various topics, including sensor/actuator networks, distributed and cloud architectures, bio-inspired systems and evolutionary approaches, methods of cognitive sensor fusion, Bayesian approaches, fuzzy systems and neural networks, biomedical applications, autonomous land, sea and air vehicles, localization, tracking, SLAM, 3D perception, manipulation with multifinger hands, robotics, micro/nano systems, information fusion and sensors, and multimodal integration in HCI and HRI. The book is intended for robotics scientists, data and information fusion scientists, researchers and professionals at universities, research institutes and laboratories.




Nanopositioning Technologies


Book Description

This book covers the state-of-the-art technologies for positioning with nanometer resolutions and accuracies, particularly those based on piezoelectric actuators and MEMS actuators. The latest advances are described, including the design of nanopositioning devices, sensing and actuation technologies and control methods for nanopositioning. This is an ideal book for mechanical and electrical engineering students and researchers; micro and nanotechnology researchers and graduate students; as well as those working in the precision instrumentation or semiconductor industries.




Handbook of Multisensor Data Fusion


Book Description

In the years since the bestselling first edition, fusion research and applications have adapted to service-oriented architectures and pushed the boundaries of situational modeling in human behavior, expanding into fields such as chemical and biological sensing, crisis management, and intelligent buildings. Handbook of Multisensor Data Fusion: Theory and Practice, Second Edition represents the most current concepts and theory as information fusion expands into the realm of network-centric architectures. It reflects new developments in distributed and detection fusion, situation and impact awareness in complex applications, and human cognitive concepts. With contributions from the world’s leading fusion experts, this second edition expands to 31 chapters covering the fundamental theory and cutting-edge developments that are driving this field. New to the Second Edition— · Applications in electromagnetic systems and chemical and biological sensors · Army command and combat identification techniques · Techniques for automated reasoning · Advances in Kalman filtering · Fusion in a network centric environment · Service-oriented architecture concepts · Intelligent agents for improved decision making · Commercial off-the-shelf (COTS) software tools From basic information to state-of-the-art theories, this second edition continues to be a unique, comprehensive, and up-to-date resource for data fusion systems designers.




Technologies for Smart Sensors and Sensor Fusion


Book Description

Exciting new developments are enabling sensors to go beyond the realm of simple sensing of movement or capture of images to deliver information such as location in a built environment, the sense of touch, and the presence of chemicals. These sensors unlock the potential for smarter systems, allowing machines to interact with the world around them in more intelligent and sophisticated ways. Featuring contributions from authors working at the leading edge of sensor technology, Technologies for Smart Sensors and Sensor Fusion showcases the latest advancements in sensors with biotechnology, medical science, chemical detection, environmental monitoring, automotive, and industrial applications. This valuable reference describes the increasingly varied number of sensors that can be integrated into arrays, and examines the growing availability and computational power of communication devices that support the algorithms needed to reduce the raw sensor data from multiple sensors and convert it into the information needed by the sensor array to enable rapid transmission of the results to the required point. Using both SI and US units, the text: Provides a fundamental and analytical understanding of the underlying technology for smart sensors Discusses groundbreaking software and sensor systems as well as key issues surrounding sensor fusion Exemplifies the richness and diversity of development work in the world of smart sensors and sensor fusion Offering fresh insight into the sensors of the future, Technologies for Smart Sensors and Sensor Fusion not only exposes readers to trends but also inspires innovation in smart sensor and sensor system development.




Sensor and Data Fusion Concepts and Applications


Book Description

First published in 1993, this Tutorial Text has been revised and updated to provide explanations and examples of data fusion algorithms in areas not covered in the first edition. These include Bayesian inference, artificial neural networks and fuzzy logic. All of the chapters in the first edition have been revised and updated and new material is included on the FASCODE and MODTRAN atmospheric models, and EOSAEL, which analyzes physical processes that affect the performance of millimeter-wave and IR sensors.




Sensor Fusion


Book Description

Sensor Fusion - Foundation and Applications comprehensively covers the foundation and applications of sensor fusion. This book provides some novel ideas, theories, and solutions related to the research areas in the field of sensor fusion. The book explores some of the latest practices and research works in the area of sensor fusion. The book contains chapters with different methods of sensor fusion for different engineering as well as non-engineering applications. Advanced applications of sensor fusion in the areas of mobile robots, automatic vehicles, airborne threats, agriculture, medical field and intrusion detection are covered in this book. Sufficient evidences and analyses have been provided in the chapter to show the effectiveness of sensor fusion in various applications. This book would serve as an invaluable reference for professionals involved in various applications of sensor fusion.




Multi-Sensor Information Fusion


Book Description

This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.