This book describes the theoretical framework of parallel manipulators and presents examples of their application. The theoretical part begins with the theory of parallel manipulator synthesis. Working on this basis, various topology designs of one-loop and multiloop parallel manipulators are then obtained. The next section describes the zero parameters method for the analysis of mechanism (manipulator) structure with closed kinematic circuits, and includes examples of its application, highlighting its advantages compared to traditional methods. The book then presents the redundant parameters method for determining the position of special parallel manipulator links, and discusses its application in solving the direct problem of link position for multiloop manipulators. It also addresses one-loop and multiloop manipulators, and includes a solution for the direct and inverse link position problems of kinematics. In closing, the book presents a range of potential applications for parallel manipulator. These examples are intended to promote the development and implementation of new engineering solutions, e.g. in seismic protection systems, renewable energy and other areas. The book includes a wealth of material that can be used for teaching undergraduate, graduate and PhD students majoring in robotics, automation and related fields, and can also be used by researchers to solve problems in connection with introducing robotics technologies.

Risk detection and cyber security play a vital role in the use and success of contemporary computing. By utilizing the latest technological advances, more effective prevention techniques can be developed to protect against cyber threats. Detecting and Mitigating Robotic Cyber Security Risks is an essential reference publication for the latest research on new methodologies and applications in the areas of robotic and digital security. Featuring extensive coverage on a broad range of topics, such as authentication techniques, cloud security, and mobile robotics, this book is ideally designed for students, researchers, scientists, and engineers seeking current research on methods, models, and implementations of optimized security in digital contexts.

This book is of interest to researchers wanting to know more about the latest topics and methods in the fields of the kinematics, control and design of robotic systems. The papers cover the full range of robotic systems, including serial, parallel and cable-driven manipulators. The systems range from being less than fully mobile, to kinematically redundant, to over-constrained. The book brings together 43 peer-reviewed papers. They report on the latest scientific and applied achievements. The main theme that connects them is the movement of robots in the most diverse areas of application.

In this practical reference, popular author Lewin Edwards shows how to develop robust, dependable real-time systems for robotics and other control applications, using open-source tools. It demonstrates efficient and low-cost embedded hardware and software design techniques, based on Linux as the development platform and operating system and the Atmel AVR as the primary microcontroller. The book provides comprehensive examples of sensor, actuator and control applications and circuits, along with source code for a number of projects. It walks the reader through the process of setting up the Linux-based controller, from creating a custom kernel to customizing the BIOS, to implementing graphical control interfaces.
Including detailed design information on:
-ESBUS PC-host interface
-Host-module communications protocol
-A speed-controlled DC motor with tach feedback and thermal cut-off
-A stepper motor controller
-A two-axis attitude sensor using a MEMS accelerometer
-Infrared remote control in Linux using LIRC
-Machine vision using Video4Linux
The Accompanying CD-ROM contains a wealth of design materials, including:
-Full schematics and source code for the projects described
-Ready-made disk images for the miniature Linux distribution uses as the basis for the PC-side software
-Distribution archives of source code for all GNU software used, along with application-specific patches where appropriate
-A free version of the schematic capture and PCB CAD software used
-Atmel AVR Studio
* The first-ever book on using open source technology for robotics design!
* Immensely valuable source code and design tools provided on the CD-ROM
* Covershot topics such as GPS navigation, 3-D sensing, and machine vision, all using a Linux platform!

This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep learning is a new area of machine learning research which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non-immediately related fields, for example between air pressure recordings and English words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g. classification) and/or unsupervised (e.g. pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition.

This book presents advanced studies on the conversion efficiency, mechanical reliability, and the quality of power related to wind energy systems. The main concern regarding such systems is reconciling the highly intermittent nature of the primary source (wind speed) with the demand for high-quality electrical energy and system stability. This means that wind energy conversion within the standard parameters imposed by the energy market and power industry is unachievable without optimization and control. The book discusses the rapid growth of control and optimization paradigms and applies them to wind energy systems: new controllers, new computational approaches, new applications, new algorithms, and new obstacles.

This book provides a unique approach to derive model-based torque controllers for all types of Lorentz force machines, i.e. DC, synchronous and induction machines. The rotating transformer model forms the basis for the generalized modeling approach of rotating field machines, which leads to the development of universal field-oriented control algorithms. Contrary to this, direct torque control algorithms, using observer-based methods, are developed for switched reluctance machines. Tutorials are included at the end of each chapter, and the reader is encouraged to execute these tutorials in order to gain familiarity with the dynamic behavior of drive systems. This updated edition uses PLECS (R) simulation and vector processing tools that were specifically adopted for the purpose of these hands-on tutorials. Hence, Advanced Electrical Drives encourages "learning by doing" and the experienced drive specialist may find the simulation tools useful to design high-performance torque controllers. Although it is a powerful reference in its own right, when used in conjunction with the companion texts Fundamentals of Electrical Drives and Applied Control of Electrical Drives, this book provides a uniquely comprehensive reference set that takes readers all the way from understanding the basics of how electrical drives work, to deep familiarity with advanced features and models, to a mastery of applying the concepts to actual hardware in practice. Teaches readers to perform insightful analysis of AC electrical machines and drives; Introduces new modeling methods and modern control techniques for switched reluctance drives; Updated to use PLECS (R) simulation tools for modeling electrical drives, including new and more experimental results; Numerous tutorials at end of each chapter to learn by doing, step-by-step; Includes extra material featuring "build and play" lab modules, for lectures and self-study.

Modelling in polymer materials science has experienced a dramatic growth in the last two decades. Advances in modeling methodologies together with rapid growth in computational power have made it possible to address increasingly complex questions both of a fundamental and of a more applied nature.
Multiscale Modelling of Polymer Properties assembles research done on modeling of polymeric materials from a hierarchical point of view, in which several methods are combined in a multilevel approach to complex polymeric materials. Contributions from academic and industrial experts are organized in two parts: the first one addresses the methodological aspects while the second one focuses on specific applications. The book aims at comprehensively assessing the current state of the field, including the strengths and shortcomings of available modelling techniques, and at identifying future needs and trends.
* Several levels of approximation to the field of polymer modelling; ranging from first-principles to purely macroscopic
* Contributions from both academic and industrial experts with varying fields of expertise
* Assesses current state of this emerging and rapidly growing field

This is the fourth volume of the successful series Robot Operating Systems: The Complete Reference, providing a comprehensive overview of robot operating systems (ROS), which is currently the main development framework for robotics applications, as well as the latest trends and contributed systems. The book is divided into four parts: Part 1 features two papers on navigation, discussing SLAM and path planning. Part 2 focuses on the integration of ROS into quadcopters and their control. Part 3 then discusses two emerging applications for robotics: cloud robotics, and video stabilization. Part 4 presents tools developed for ROS; the first is a practical alternative to the roslaunch system, and the second is related to penetration testing. This book is a valuable resource for ROS users and wanting to learn more about ROS capabilities and features.

This book presents a variety of perspectives on vision-based applications. These contributions are focused on optoelectronic sensors, 3D & 2D machine vision technologies, robot navigation, control schemes, motion controllers, intelligent algorithms and vision systems. The authors focus on applications of unmanned aerial vehicles, autonomous and mobile robots, industrial inspection applications and structural health monitoring. Recent advanced research in measurement and others areas where 3D & 2D machine vision and machine control play an important role, as well as surveys and reviews about vision-based applications. These topics are of interest to readers from diverse areas, including electrical, electronics and computer engineering, technologists, students and non-specialist readers. * Presents current research in image and signal sensors, methods, and 3D & 2D technologies in vision-based theories and applications; * Discusses applications such as daily use devices including robotics, detection, tracking and stereoscopic vision systems, pose estimation, avoidance of objects, control and data exchange for navigation, and aerial imagery processing; * Includes research contributions in scientific, industrial, and civil applications.

The book focuses the latest endeavours relating researches and developments conducted in fields of Control, Robotics and Automation. Through more than twenty revised and extended articles, the present book aims to provide the most up-to-date state-of-art of the aforementioned fields allowing researcher, PhD students and engineers not only updating their knowledge but also benefiting from the source of inspiration that represents the set of selected articles of the book. The deliberate intention of editors to cover as well theoretical facets of those fields as their practical accomplishments and implementations offers the benefit of gathering in a same volume a factual and well-balanced prospect of nowadays research in those topics. A special attention toward "Intelligent Robots and Control" may characterize another benefit of this book.

This book shows in a comprehensive presentation how Bond Graph methodology can support model-based control, model-based fault diagnosis, fault accommodation, and failure prognosis by reviewing the state-of-the-art, presenting a hybrid integrated approach to Bond Graph model-based fault diagnosis and failure prognosis, and by providing a review of software that can be used for these tasks. The structured text illustrates on numerous small examples how the computational structure superimposed on an acausal bond graph can be exploited to check for control properties such as structural observability and control lability, perform parameter estimation and fault detection and isolation, provide discrete values of an unknown degradation trend at sample points, and develop an inverse model for fault accommodation. The comprehensive presentation also covers failure prognosis based on continuous state estimation by means of filters or time series forecasting. This book has been written for students specializing in the overlap of engineering and computer science as well as for researchers, and for engineers in industry working with modelling, simulation, control, fault diagnosis, and failure prognosis in various application fields and who might be interested to see how bond graph modelling can support their work. Presents a hybrid model-based, data-driven approach to failure prognosis Highlights synergies and relations between fault diagnosis and failure prognostic Discusses the importance of fault diagnosis and failure prognostic in various fields

Approximation Methods in Engineering and Science covers fundamental and advanced topics in three areas: Dimensional Analysis, Continued Fractions, and Stability Analysis of the Mathieu Differential Equation. Throughout the book, a strong emphasis is given to concepts and methods used in everyday calculations. Dimensional analysis is a crucial need for every engineer and scientist to be able to do experiments on scaled models and use the results in real world applications. Knowing that most nonlinear equations have no analytic solution, the power series solution is assumed to be the first approach to derive an approximate solution. However, this book will show the advantages of continued fractions and provides a systematic method to develop better approximate solutions in continued fractions. It also shows the importance of determining stability chart of the Mathieu equation and reviews and compares several approximate methods for that. The book provides the energy-rate method to study the stability of parametric differential equations that generates much better approximate solutions.

This book focuses on the fault diagnosis observer design for the switched system. Model-based fault diagnosis and fault tolerant control are one of the most popular research directions in recent decades. It contains eight chapters. Every chapter is independent in the method of observer design, but all chapters are around the same topic. Besides, in each chapter, the model description and theoretical results are firstly provided, then some practical application examples are illustrated to prove the obtained results. The advanced theoretical methodologies will benefit researchers or engineers in the area of safety engineering and the arrangement of the structure will help the readers to understand the content easily.

This book provides exclusive insight into the development of a new generation of robotic underwater technologies. Deploying and using even the most simple and robust mechanical tools is presenting a challenge, and is often associated with an enormous amount of preparation, continuous monitoring, and maintenance. Therefore, all disciplinary aspects (e.g. system design, communication, machine learning, mapping and coordination, adaptive mission planning) are examined in detail and together this gives an extensive overview on research areas influencing next generation underwater robots. These robotic underwater systems will operate autonomously with the help of the most modern artificial intelligence procedures and perform environmental monitoring as well as inspection and maintenance of underwater structures. The systems are designed as modular and reconfigurable systems for long term autonomy to remain at the site for longer periods of time. New communication methods using AI enable missions of hybrid teams of humans and heterogeneous robots. Thus this volume will be an important reference for scientists on every qualification level in the field of underwater technologies, industrial maritime applications, and maritime science.

This book proposes some novel approaches for finding unmanned aerial vehicle trajectories to reach targets with unknown location in minimum time. At first, it reviews probabilistic search algorithms that have been used for dealing with the minimum time search (MTS) problem, and discusses how metaheuristics, and in particular the ant colony optimization algorithm (ACO), can help to find high-quality solutions with low computational time. Then, it describes two ACO-based approaches to solve the discrete MTS problem and the continuous MTS problem, respectively. In turn, it reports on the evaluation of the ACO-based discrete and continuous approaches to the MTS problem in different simulated scenarios, showing that the methods outperform in most all the cases over other state-of-the-art approaches. In the last part of the thesis, the work of integration of the proposed techniques in the ground control station developed by Airbus to control ATLANTE UAV is reported in detail, providing practical insights into the implementation of these methods for real UAVs.

This book offers a comprehensive reference guide for modeling humanoid robots using intelligent and fuzzy systems. It provides readers with the necessary intelligent and fuzzy tools for controlling humanoid robots by incomplete, vague, and imprecise information or insufficient data, where classical modeling approaches cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including fuzzy control, metaheuristic-based control, neutrosophic control, etc. To foster reader comprehension, all chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers, and postgraduate students pursuing research on humanoid robots. Moreover, by extending all the main aspects of humanoid robots to its intelligent and fuzzy counterparts, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas, and developments.

This book gathers contributions from a multidisciplinary research team comprised of control engineering and economics researchers and formed to address a central interdisciplinary social issue, namely economically enabled energy management. The book's primary focus is on achieving optimal energy management that is viable from both an engineering and economic standpoint. In addition to the theoretical results and techniques presented, several chapters highlight experimental case studies, which will benefit academic researchers and practitioners alike. The first three chapters present comprehensive overviews of respective social contexts, underscore the pressing need for economically efficient energy management systems and academic work on this emerging research topic, and identify fundamental differences between approaches in control engineering and economics. In turn, the next three chapters (Chapters 4-6) provide economics-oriented approaches to the subject. The following five chapters (Chapters 7-11) address optimal energy market design, integrating both physical and economic models. The book's last three chapters (Chapters 12-14) mainly focus on the engineering aspects of next-generation energy management, though economic factors are also shown to play important roles.

This book shows how a conventional multi-layered approach can be used to control a snake robot on a desired path while moving on a flat surface. To achieve robustness to unknown variations in surface conditions, it explores various adaptive robust control methods. The authors propose a sliding-mode control approach designed to achieve robust maneuvering for bounded uncertainty with a known upper bound. The control is modified by addition of an adaptation law to alleviate the overestimation problem of the switching gain as well as to circumvent the requirement for knowledge regarding the bounds of uncertainty. The book works toward non-conservativeness, achieving efficient tracking in the presence of slowly varying uncertainties with a specially designed framework for time-delayed control. It shows readers how to extract superior performance from their snake robots with an approach that allows robustness toward bounded time-delayed estimation errors. The book also demonstrates how the multi-layered control framework can be simplified by employing differential flatness for such a system. Finally, the mathematical model of a snake robot moving inside a uniform channel using only side-wall contact is discussed. The model has further been employed to demonstrate adaptive robust control design for such a motion. Using numerous illustrations and tables, Adaptive Robust Control for Planar Snake Robots will interest researchers, practicing engineers and postgraduate students working in the field of robotics and control systems.

This multi-volume handbook is the most up-to-date and comprehensive reference work in the field of fractional calculus and its numerous applications. This sixth volume collects authoritative chapters covering several applications of fractional calculus in control theory, including fractional controllers, design methods and toolboxes, and a large number of engineering applications of control.

Intelligent Control techniques are becoming important tools in both academia and industry. Methodologies developed in the field of soft-computing, such as neural networks, fuzzy systems and evolutionary computation, can lead to accommodation of more complex processes, improved performance and considerable time savings and cost reductions. "Intelligent Control Systems Using Computational Intelligence Techniques" details the application of these tools to the field of control systems. Each chapter gives an overview of current approaches in the topic covered, with a set of the most important set references in the field, and then details the author s approach, examining both the theory and practical applications."

This book discusses systematic designs of stable adaptive fuzzy logic controllers employing hybridizations of Lyapunov strategy-based approaches/H theory-based approaches and contemporary stochastic optimization techniques. The text demonstrates how candidate stochastic optimization techniques like Particle swarm optimization (PSO), harmony search (HS) algorithms, covariance matrix adaptation (CMA) etc. can be utilized in conjunction with the Lyapunov theory/H theory to develop such hybrid control strategies. The goal of developing a series of such hybridization processes is to combine the strengths of both Lyapunov theory/H theory-based local search methods and stochastic optimization-based global search methods, so as to attain superior control algorithms that can simultaneously achieve desired asymptotic performance and provide improved transient responses. The book also demonstrates how these intelligent adaptive control algorithms can be effectively utilized in real-life applications such as in temperature control for air heater systems with transportation delay, vision-based navigation of mobile robots, intelligent control of robot manipulators etc.

This book discusses the parametric modeling, performance evaluation, design optimization and comparative study of the high-speed, parallel pick-and-place robots. It collects the modeling methodology, evaluation criteria and design guidelines for parallel PnP robots to provide a systematic analysis method for robotic developers. Furthermore, it gathers the research results previously scattered in many prestigious international journals and conference proceedings and methodically edits them and presents them in a unified form. The book is of interest to researchers, R&D engineers and graduate students in industrial parallel robotics who wish to learn the core principles, methods, algorithms, and applications.

This book focuses on the calculus of variations, including fundamental theories and applications. This textbook is intended for graduate and higher-level college and university students, introducing them to the basic concepts and calculation methods used in the calculus of variations. It covers the preliminaries, variational problems with fixed boundaries, sufficient conditions of extrema of functionals, problems with undetermined boundaries, variational problems of conditional extrema, variational problems in parametric forms, variational principles, direct methods for variational problems, variational principles in mechanics and their applications, and variational problems of functionals with vector, tensor and Hamiltonian operators. Many of the contributions are based on the authors' research, addressing topics such as the extension of the connotation of the Hilbert adjoint operator, definitions of the other three kinds of adjoint operators, the extremum function theorem of the complete functional, unified Euler equations in variational methods, variational theories of functionals with vectors, modulus of vectors, arbitrary order tensors, Hamiltonian operators and Hamiltonian operator strings, reconciling the Euler equations and the natural boundary conditions, and the application range of variational methods. The book is also a valuable reference resource for teachers as well as science and technology professionals.

This book is based on the authors' research on the stabilization and fault-tolerant control of batch processes, which are flourishing topics in the field of control system engineering. It introduces iterative learning control for linear/nonlinear single/multi-phase batch processes; iterative learning optimal guaranteed cost control; delay-dependent iterative learning control; and iterative learning fault-tolerant control for linear/nonlinear single/multi-phase batch processes. Providing important insights and useful methods and practical algorithms that can potentially be applied in batch process control and optimization, it is a valuable resource for researchers, scientists, and engineers in the field of process system engineering and control engineering.