![]() |
Welcome to Loot.co.za!
Sign in / Register |Wishlists & Gift Vouchers |Help | Advanced search
|
Your cart is empty |
||
|
Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering
This book tackles the latest research trends in technology acceptance models and theories. It presents high-quality empirical and review studies focusing on the main theoretical models and their applications across various technologies and contexts. It also provides insights into the theoretical and practical aspects of different technological innovations that assist decision-makers in formulating the required policies and procedures for adopting a specific technology.
This book introduces intelligent manufacturing system planning, design, and implementation, through the deep integration of the Internet, big data, artificial intelligence, and manufacturing process, to promote the transformation and upgrading of enterprises. This book shows the implementation of intelligent manufacturing process with 12 benchmarking enterprises, discusses the planning, implementation, and control of intelligent manufacturing system technology and method of theory, and analyzes the five hierarchies of intelligent manufacturing system, the five stages of life cycle, and five kinds of intelligent depth. The content can cultivate the reader's vocational ability to develop intelligent solutions and implementation based on complex, uncertain environment needs. This book will be interesting and useful to a wide readership in the various fields of management, information science, and engineering science.
This book includes high-quality research papers presented at Symposium on Power Electronic and Renewable Energy Systems Control (PERESC 2020), which is held at the School of Electrical Sciences, IIT Bhubaneswar, Odisha, India, during 4-5 December 2020. The book covers original work in power electronics which has greatly enabled integration of renewable and distributed energy systems, control of electric machine drives, high voltage system control and operation. The book is highly useful for academicians, engineers, researchers and students to be familiar with the latest state of the art in power electronics technology and its applications.
This book introduces modeling and simulation of linear time invariant systems and demonstrates how these translate to systems engineering, mechatronics engineering, and biomedical engineering. It is organized into nine chapters that follow the lectures used for a one-semester course on this topic, making it appropriate for students as well as researchers. The author discusses state space modeling derived from two modeling techniques and the analysis of the system and usage of modeling in control systems design. It also contains a unique chapter on multidisciplinary energy systems with a special focus on bioengineering systems and expands upon how the bond graph augments research in biomedical and bio-mechatronics systems.
This book focuses on the principles and technology of environmental perception in unmanned systems. With the rapid development of a new generation of information technologies such as automatic control and information perception, a new generation of robots and unmanned systems will also take on new importance. This book first reviews the development of autonomous systems and subsequently introduces readers to the technical characteristics and main technologies of the sensor. Lastly, it addresses aspects including autonomous path planning, intelligent perception and autonomous control technology under uncertain conditions. For the first time, the book systematically introduces the core technology of autonomous system information perception.
Tactile Sensing, Skill Learning and Robotic Dexterous Manipulation focuses on cross-disciplinary lines of research and groundbreaking research ideas in three research lines: tactile sensing, skill learning and dexterous control. The book introduces recent work about human dexterous skill representation and learning, along with discussions of tactile sensing and its applications on unknown objects' property recognition and reconstruction. Sections also introduce the adaptive control schema and its learning by imitation and exploration. Other chapters describe the fundamental part of relevant research, paying attention to the connection among different fields and showing the state-of-the-art in related branches. The book summarizes the different approaches and discusses the pros and cons of each. Chapters not only describe the research but also include basic knowledge that can help readers understand the proposed work, making it an excellent resource for researchers and professionals who work in the robotics industry, haptics and in machine learning.
As control systems become more complex and are expected to perform tasks in unknown and extreme environments, they may be subject to various types of faults in their sensors, actuators or other components. It is crucial to be able to diagnose the occurrence of faults and to repair them in order to maintain, guarantee, and improve the overall safety, reliability, and performance of the systems. This book addresses the design challenges of developing and implementing novel integrated fault diagnosis and control technologies for complex linear systems. Integrated Fault Diagnosis and Control Design of Linear Complex Systems considers linear time-invariant (LTI) systems under both time- and event-triggered frameworks. The book initially develops novel methodologies for the problem of integrated fault diagnosis and control of LTI systems to address current design challenges. The results obtained are then extended to a number of complex linear systems, specifically to Markovian jump systems as well as to cooperative multi-agent systems.
"Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems" discusses new and meaningful findings on robust output feedback H-infinity control and filtering for uncertain linear systems, presenting a number of useful and less conservative design results based on the linear matrix inequality (LMI) technique. Though primarily intended for graduate students in control and filtering, the book can also serve as a valuable reference work for researchers wishing to explore the area of robust H-infinity control and filtering of uncertain systems. Dr. Xiao-Heng Chang is a Professor at the College of Engineering, Bohai University, China.
This monograph introduces breakthrough control algorithms for partial differential equation models with moving boundaries, the study of which is known as the Stefan problem. The algorithms can be used to improve the performance of various processes with phase changes, such as additive manufacturing. Using the authors' innovative design solutions, readers will also be equipped to apply estimation algorithms for real-world phase change dynamics, from polar ice to lithium-ion batteries. A historical treatment of the Stefan problem opens the book, situating readers in the larger context of the area. Following this, the chapters are organized into two parts. The first presents the design method and analysis of the boundary control and estimation algorithms. Part two then explores a number of applications, such as 3D printing via screw extrusion and laser sintering, and also discusses the experimental verifications conducted. A number of open problems and provided as well, offering readers multiple paths to explore in future research. Materials Phase Change PDE Control & Estimation is ideal for researchers and graduate students working on control and dynamical systems, and particularly those studying partial differential equations and moving boundaries. It will also appeal to industrial engineers and graduate students in engineering who are interested in this area.
This book presents best selected papers presented at the 4th International Conference on Smart Computing and Informatics (SCI 2020), held at the Department of Computer Science and Engineering, Vasavi College of Engineering (Autonomous), Hyderabad, Telangana, India. It presents advanced and multi-disciplinary research towards the design of smart computing and informatics. The theme is on a broader front which focuses on various innovation paradigms in system knowledge, intelligence and sustainability that may be applied to provide realistic solutions to varied problems in society, environment and industries. The scope is also extended towards the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology and health care.
Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks.
This book presents the human, cultural, and scientific contributions of professor Eliano Pessa, who recently passed away. His research interests and activities were varied, some of which included quantum physics, cognitive science and psychology, systems science, artificial intelligence, and alpinism. They were never disciplinary-separated issues, but rather some coherent dimensions of his interests in life. He lived and not only practiced interdisciplinarity and multiple dimensions; he considered it unacceptable to do only one thing in life. The contributors in this volume consider, discuss, interpret, and represent the multiplicity and interdisciplinarity experienced, lived and applied by Pessa. The chapters are inspired by, rebuild, and retrace such networked interests lived by him from the personal, cultural, and scientific points of view of the authors. This is true interdisciplinarity and usage of non-equivalences, honoring the richness of Pessa's contributions.
This fascinating book examines some of the characteristics of
technological/engineering models that are likely to be unfamiliar
to those who are interested primarily in the history and philosophy
of science and mathematics, and which differentiate technological
models from scientific and mathematical ones. Themes that are
highlighted include:
This book examines key issues in improving the efficiency of small and medium power boiler units by adding control systems for the fuel combustion process. The original models, algorithms, software and hardware of the system developed for controlling the fuel combustion process are presented. In turn, the book presents a methodology for assessing the influence of climatic factors on the combustion process, and proposes new methods for measuring the thermophysical characteristics, which require taking into account the concentration of oxygen in the air. The system developed here was implemented on a boiler of the NIISTU-5 type, which is widely used for heat power engineering in Ukraine and other Eastern European countries. Given its scope, the book offers a valuable asset for researchers and engineers, as well as lecturers and graduate students at higher education institutions dealing with heat engineering equipment.
This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non-invasive means. Intelligent Feature Selection for Machine Learning using the Dynamic Wavelet Fingerprint begins by providing background information on machine learning and the wavelet fingerprint technique. It then progresses through six technical chapters, applying the methods discussed to particular real-world problems. Theses chapters are presented in such a way that they can be read on their own, depending on the reader's area of interest, or read together to provide a comprehensive overview of the topic. Given its scope, the book will be of interest to practitioners, engineers and researchers seeking to leverage the latest advances in machine learning in order to develop solutions to practical problems in structural health monitoring, medical imaging, autonomous vehicles, wireless technology, and historical conservation.
This book examines the burgeoning revolution in the construction industry known as Construction 4.0, the attendant need for re-skilling human resources, and key stakeholders' roles in developing the required skills for Construction 4.0. It views the lack of 21st-century skills and skills gap in the industry as significant challenges limiting the uptake and implementation of Construction 4.0 technologies, especially in developing countries. In order to determine the skills required, this book examines the critical technologies of Construction 4.0, such as building information modelling (BIM), robotic construction, 3D printing and drones, which have transformed the construction industry, thereby creating digital, intelligent and sustainable construction solutions. Furthermore, the book considers the benefits, risks and relevant skills required to implement Construction 4.0 technologies.
This monograph explores the analysis and design of model-free optimal control systems based on reinforcement learning (RL) theory, presenting new methods that overcome recent challenges faced by RL. New developments in the design of sensor data efficient RL algorithms are demonstrated that not only reduce the requirement of sensors by means of output feedback, but also ensure optimality and stability guarantees. A variety of practical challenges are considered, including disturbance rejection, control constraints, and communication delays. Ideas from game theory are incorporated to solve output feedback disturbance rejection problems, and the concepts of low gain feedback control are employed to develop RL controllers that achieve global stability under control constraints. Output Feedback Reinforcement Learning Control for Linear Systems will be a valuable reference for graduate students, control theorists working on optimal control systems, engineers, and applied mathematicians.
The proceedings of the 4th Stability and Control Processes Conference are focused on modern applied mathematics, stability theory, and control processes. The conference was held in recognition of the 90th birthday of Professor Vladimir Ivanovich Zubov (1930-2000). This selection of papers reflects the wide-ranging nature of V. I. Zubov's work, which included contributions to the development of the qualitative theory of differential equations, the theory of rigid body motion, optimal control theory, and the theory of electromagnetic fields. It helps to advance many aspects of the theory of control systems, including questions of motion stability, nonlinear oscillations in control systems, navigation and reliability of control devices, vibration theory, and quantization of orbits. The disparate applications covered by the book - in mechanical systems, game theory, solid-state physics, socio-economic systems and medical and biological systems, control automata and navigation - are developments from Professor Zubov's in-depth studies on the theory of stability of motion, the theory of automatic control and the theory of the motions of optimal processes. Stability and Control Processes presents research continuing the legacy of V. I. Zubov and updates it with sections focused on intelligence-based control. These proceedings will be of interest to academics, professionals working in industry and researchers alike.
The book presents an overview of current research on biologically inspired autonomous robotics from the perspective of some of the most relevant researchers in this area. The book crosses several boundaries in the field of robotics and the closely related field of artificial life. The key aim throughout the book is to obtain autonomy at different levels. From the basic motor behavior in some exotic robot architectures right through to the planning of complex behaviors or the evolution of robot control structures, the book explores different degrees and definitions of autonomous behavior. These behaviors are supported by a wide variety of modeling techniques: structural grammars, neural networks, and fuzzy logic and evolution underlies many of the development processes. Thus this text can be used by scientists and students interested in these areas and provides a general view of the field for a more general audience.
The proceedings present selected research papers from the CIAC2021, held in Zhanjiang, China on Nov 5-7, 2021. It covers a wide range of topics including intelligent control, robotics, artificial intelligence, pattern recognition, unmanned systems, IoT and machine learning. It includes original research and the latest advances in the field of intelligent automation. Engineers and researchers from academia, industry, and government can gain valuable insights into solutions combining ideas from multiple disciplines in this field.
This book intends to introduce some recent results on passivity of complex dynamical networks with single weight and multiple weights. The book collects novel research ideas and some definitions in complex dynamical networks, such as passivity, output strict passivity, input strict passivity, finite-time passivity, and multiple weights. Furthermore, the research results previously published in many flagship journals are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers and graduate students in Engineering and Mathematics who wish to study the passivity of complex dynamical networks.
This book reports the new results of intelligent robot with hand-eye-brain, from the interdisciplinary perspective of information science and neuroscience. It collects novel research ideas on attractive region in environment (ARIE), intrinsic variable preserving manifold learning (IVPML) and biologically inspired visual congnition, which are theoretically important but challenging to develop the intelligent robot. Furthermore, the book offers new thoughts on the possible future development of human-inspired robotics, with vivid illustrations. The book is useful for researchers, R&D engineers and graduate students working on intelligent robots.
This book presents operational and practical issuesof automotive mechatronics with special emphasis on the heterogeneous automotive vehicle systems approach, and is intended as a graduate text as well as a reference for scientists and engineers involved in the design of automotive mechatronic control systems. As the complexity of automotive vehicles increases, so does the dearth of high competence, multi-disciplined automotive scientists and engineers. This book provides a discussion into the type of mechatronic control systems found in modernvehicles and the skills required by automotive scientists and engineers working in this environment. Divided into two volumes and five parts, "Automotive Mechatronics" aimsat improving automotive mechatronics education and emphasises the trainingof students experimental hands-on abilities, stimulating and promoting experience among high education institutes and produce more automotive mechatronics and automation engineers. The main subject that are treated are: VOLUME I: RBW or XBW unibody or chassis-motion mechatronic control hypersystems;DBW AWD propulsion mechatronic control systems; BBW AWB dispulsion mechatronic control systems; VOLUME II: SBW AWS diversion mechatronic control systems; ABW AWA suspension mechatronic control systems. This volumewas developed for undergraduate and postgraduate students as wellas for professionals involved in all disciplines related to the design or research and development of automotive vehicle dynamics, powertrains, brakes, steering, and shock absorbers (dampers). Basic knowledge of college mathematics, college physics, and knowledge of the functionality of automotive vehicle basic propulsion, dispulsion, conversion and suspension systems is required. "
This book belongs to the subject of control and systems theory. The discrete-time adaptive iterative learning control (DAILC) is discussed as a cutting-edge of ILC and can address random initial states, iteration-varying targets, and other non-repetitive uncertainties in practical applications. This book begins with the design and analysis of model-based DAILC methods by referencing the tools used in the discrete-time adaptive control theory. To overcome the extreme difficulties in modeling a complex system, the data-driven DAILC methods are further discussed by building a linear parametric data mapping between two consecutive iterations. Other significant improvements and extensions of the model-based/data-driven DAILC are also studied to facilitate broader applications. The readers can learn the recent progress on DAILC with consideration of various applications. This book is intended for academic scholars, engineers and graduate students who are interested in learning control, adaptive control, nonlinear systems, and related fields.
Technology has created innovative new prospects for manufacturing industries with Industry 4.0 and has helped further the growth of the manufacturing sector. This book focuses on the next stage, which is Industry 5.0, and the steps in taking automation to that next level by increasing processes and operational efficiency, as well as reducing workforce size. Industry 5.0: The Future of the Industrial Economy discusses the integration of product, process, machine, software, and industrial robots in realizing Industry 5.0. It covers the dual integration of human intelligence with machine intelligence and reviews the results of making use of Industrial Internet of Things (IIoT) and Artificial Intelligence (AI). The creation of a new category of robots named Collaborative Robots (Cobots) specifically designed to speed up the manufacturing process and profitability is explored. This book also explores how to reduce waste in product design through the manufacturing process and offers more personalized and customized products for customers. Manufacturing, design, industrial, and mechanical engineers, as well as practicing professionals, will find this book of interest. Management executives, CIOs, CEOs, IT professionals, and academics will also find something of value in this book that takes Industry 4.0 to Industry 5.0 and beyond. |
You may like...
Artificial Intelligence for Future…
Rabindra Nath Shaw, Ankush Ghosh, …
Paperback
R3,864
Discovery Miles 38 640
|