Surveillance systems have become increasingly popular. Full involvement of human operators has led to shortcomings, e.g. high labor cost, limited capability for multiple screens, inconsistency in long-duration, etc. Intelligent surveillance systems (ISSs) can supplement or even replace traditional ones. In ISSs, computer vision, pattern recognition, and artificial intelligence technologies are used to identify abnormal behaviours in videos. They present the development of real-time behaviour-based intelligent surveillance systems. The book focuses on the detection of individual abnormal behaviour based on learning and the analysis of dangerous crowd behaviour based on texture and optical flow. Practical systems include a real-time face classification and counting system, a surveillance robot system that utilizes video and audio information for intelligent interaction, and a robust person counting system for crowded environments.

The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamics. The book includes numerous references to the most recent literature. Many methods are illustrated by numerical examples or experimental results.

Real-Time Systems in Mechatronic Applications brings together in one place important contributions and up-to-date research results in this fast moving area. Real-Time Systems in Mechatronic Applications serves as an excellent reference, providing insight into some of the most challenging research issues in the field.

This book is devoted to a novel conceptual theoretical framework of neuro science and is an attempt to show that we can postulate a very small number of assumptions and utilize their heuristics to explain a very large spectrum of brain phenomena. The major assumption made in this book is that inborn and acquired neural automatisms are generated according to the same func tional principles. Accordingly, the principles that have been revealed experi mentally to govern inborn motor automatisms, such as locomotion and scratching, are used to elucidate the nature of acquired or learned automat isms. This approach allowed me to apply the language of control theory to describe functions of biological neural networks. You, the reader, can judge the logic of the conclusions regarding brain phenomena that the book derives from these assumptions. If you find the argument flawless, one can call it common sense and consider that to be the best praise for a chain of logical conclusions. For the sake of clarity, I have attempted to make this monograph as readable as possible. Special attention has been given to describing some of the concepts of optimal control theory in such a way that it will be under standable to a biologist or physician. I have also included plenty of illustra tive examples and references designed to demonstrate the appropriateness and applicability of these conceptual theoretical notions for the neurosciences."

Real-world supply chains and networks are inherently complex, formed by a large number of self-governing interconnected agents which dynamically update their behavior rules and connections based on context and environment changes. Oftentimes, these complex systems fail, almost inexplicably, due to unforeseen events leading to disruption. Exploration and research of the mechanisms behind the failure of supply chains and networks have revealed that those capable of surviving are not only robust, but resilient. The purpose of this book is to explain the meaning of resilience and its design in the broad context, and with a focus on the design and management of supply chains and supply networks. Written by Dr. Reyes Levalle, an experienced supply chains designer and supply networks engineer, the book is intended for beginners and advanced professionals, students, designers, policy makers, and managers. It is a pioneering effort to base resilience engineering and management on CCT, the collaborative control theory and tools.

This book provides a comprehensive treatment of the principles underlying optimal constrained control and estimation. The contents progress from optimisation theory, fixed-horizon discrete optimal control, receding-horizon implementations and stability conditions to explicit solutions and numerical algorithms, moving horizon estimation, and connections between constrained estimation and control. Several case studies and further developments illustrate and expand the core principles.

Specific topics covered include:

a [ An overview of optimisation theory.

a [ Links to optimal control theory, including the discrete-minimum principle.

a [ Linear and nonlinear receding-horizon constrained control including stability.

a [ Constrained control solutions having a finite parameterisation for specific classes of problems.

a [ Numerical procedures for solving constrained optimisation problems.

a [ Output feedback optimal constrained control.

a [ Constrained state estimation.

a [ Duality between constrained estimation and control.

a [ Applications to finite alphabet control and estimation problems, cross-directional control, rudder-roll stabilisation of ships, and control over communication networks.

Constrained Control and Estimation is a self-contained treatment assuming that the reader has a basic background in systems theory, including linear control, stability and state-space methods. It is suitable for use in senior-level courses and as material for reference and self-study. A companion website is continually updated by the authors.

Neural Networks in Robotics is the first book to present an integrated view of both the application of artificial neural networks to robot control and the neuromuscular models from which robots were created. The behavior of biological systems provides both the inspiration and the challenge for robotics. The goal is to build robots which can emulate the ability of living organisms to integrate perceptual inputs smoothly with motor responses, even in the presence of novel stimuli and changes in the environment. The ability of living systems to learn and to adapt provides the standard against which robotic systems are judged. In order to emulate these abilities, a number of investigators have attempted to create robot controllers which are modelled on known processes in the brain and musculo-skeletal system. Several of these models are described in this book. On the other hand, connectionist (artificial neural network) formulations are attractive for the computation of inverse kinematics and dynamics of robots, because they can be trained for this purpose without explicit programming. Some of the computational advantages and problems of this approach are also presented. For any serious student of robotics, Neural Networks in Robotics provides an indispensable reference to the work of major researchers in the field. Similarly, since robotics is an outstanding application area for artificial neural networks, Neural Networks in Robotics is equally important to workers in connectionism and to students for sensormonitor control in living systems.

This book addresses the design of compliant mechanisms, presenting readers with a good understanding of both the solid mechanics of flexible elements and their configuration design, based on a mechanism-equivalent approach in the framework of screw theory. The book begins with the theoretical background of screw theory, and systematically addresses both the compliance characteristics of flexible elements and their configuration design. The book then covers a broad range of compliant parallel mechanism design topics, from stiffness to constraint decomposition, from conceptual design to dimensional design, and from analysis to synthesis, as well as the large deformation problem; this is followed by both simulations and physical experiments, offering readers a solid foundation and useful tools. Given its scope and the results it presents, the book will certainly benefit and inform future research on the topic. It offers a valuable asset for researchers, developers, engineers and graduate students with an interest in compliant mechanisms, robotics and screw theory.

For courses in Programmable Logic Controllers where the Allen/Bradley programmable logic controller is the controller of choice. This text focuses on the theory and operation of PLC systems with an emphasis on program analysis and development. The book is written in easy-to-read and understandable language with many crisp illustrations and practical examples. It describes the PLC instructions for the Allen-Bradley PLC 5, SLC 500, and Logix processors with an emphasis on the SLC 500 system using numerous figures, tables, and example problems. The text features a new two-column and four-color interior design that improves readability and figure placement. The book's organization also has improved; all the chapter questions and problems are listed in one convenient location in Appendix D with page locations for all chapter references in the questions and problems. This book describes the technology in a clear, concise style that is effective in helping students who have no previous experience in PLCs or discrete and analog system control. For additional resources, visit these web sites: http: //plctext.com/ http: //plcteacher.c

The problem of asymptotic regulation of the output of a dynamical system plays a central role in control theory. An important variant of this problem is the output regulation problem, which can be used in such areas as set-point control, tracking reference signals and rejecting disturbances generated by an external system, controlled synchronization of dynamical systems, and observer design for autonomous systems. This book is one of the first systematic studies on the nonlinear output regulation problem that embraces both the local and global solvability analysis, covering such aspects as solvability conditions, controller design, and practical implementation issues.

The book opens with the development of the mathematical apparatus of convergent systemsa "very useful for studying nonlinear control systemsa "laying the foundation for most of the results presented in the work. The study then proceeds to a new problem statementa "the so-called uniform output regulation problem. A comprehensive solvability analysis of this problem is provided in the next part of the work. Based on the solvability analysis, constructive controller design methods for the global uniform output regulation problem are presented for various classes of nonlinear systems.

In an attempt to bridge the gap between theory and practice, the authors conclude with a presentation of an experimental case study. The experimenta "one of the first in the field of nonlinear output regulationa "deals with control of a translational oscillator with a rotational actuator, illustrating the applicability of the nonlinear output regulation theory in experiments and raising a number of questions to be addressed in futureresearch.

The scope of questions addressed in the book, the uniformity of their treatment, the novelty of the proposed approach, and the obtained results make this volume unique with respect to other works on the problem of nonlinear output regulation. In addition to being an excellent reference for the uniform output regulation problem, the book has a tutorial value on convergent systems. The work will be of interest to control engineers, theorists, and students, and may be used as a textbook for a graduate course on nonlinear control.

The book focuses on Pareto optimality in cooperative games. Most of the existing works focus on the Pareto optimality of deterministic continuous-time systems or for the regular convex LQ case. To expand on the available literature, we explore the existence conditions of Pareto solutions in stochastic differential game for more general cases. In addition, the LQ Pareto game for stochastic singular systems, Pareto-based guaranteed cost control for uncertain mean-field stochastic systems, and the existence conditions of Pareto solutions in cooperative difference game are also studied in detail. Addressing Pareto optimality for more general cases and wider systems is one of the major features of the book, making it particularly suitable for readers who are interested in multi-objective optimal control. Accordingly, it offers a valuable asset for researchers, engineers, and graduate students in the fields of control theory and control engineering, economics, management science, mathematics, etc.

In the last decade, we have seen an extraordinary progress in the the ory and applications of robot kinematics. This has been motivated espe cially by the development of complex parallel and humanoid robots. The present book reports the most recent research advances in the theory, design, control and application of robotic systems, which are intended for a variety of purposes such as manipulation, manufacturing, automa tion, surgery, locomotion and biomechanics. The issues addressed are fundamentally kinematic in nature, including synthesis, calibration, re dundancy, force control, dexterity, inverse and forward kinematics, kine matic singularities, as well as over-constrained systems. Methods used include line geometry, quaternion algebra, screw algebra, and linear alge bra. These methods are applied to both parallel and serial multi-degree of-freedom systems. The results should interest researchers, teachers and students, in fields of engineering and mathematics related to robot theory, design, control and application. This is the sixth book of the series Advances in Robot Kinematics published by Kluwer. The contributions in this book had been rigorously reviewed by in dependent reviewers and fifty one articles had been recommended for publication. They were introduced in seven chapters. These articles were also reported and discussed at the ninth international symposium on Advances in Robot Kinematics which was held in June 2004 in Sestri Levante in Italy. Indexed in Conference Proceedings Citation Index- Science (CPCI-S)

This book aims at reporting some of the most challenging open problems of control theoretic nature raised by robotics applications. Topics covered in the book represent many of the most innovative areas in contemporary robotics research, with special emphasis on vision, sensory-feedback control, human-centered robotics, manipulation, planning, flexible and cooperative robots, or assembly systems. The basic idea behind the book is to present the variety of innovative applications and related technology demands that arise from robotics and automation to a larger community, including in particular, researchers in automatic control, applied mathematics, mechanical engineering, or computer science. The book is intended for an audience of researchers and graduate students in those disciplines and in robotics. It is the outcome of a workshop held in Las Vegas, Nevada on December 14, 2002 jointly sponsored by the IEEE Control Systems Society and the IEEE Robotics and Automation Society.

H-infinity control theory deals with the minimization of the H-infinity-norm of the transfer matrix from an exogenous disturbance to a pertinent controlled output of a given plant. Robust and H-infinity Control examines both the theoretical and practical aspects of H-infinity control from the angle of the structural properties of linear systems.

Constructive algorithms are provided for finding solutions to:

a [ general singular H-infinity control problems;

a [ general H-infinity almost disturbance decoupling problems;

a [ robust and perfect tracking problems.

The theory presented in the earlier chapters of the text are also subsequently applied to real-life problems with actual implementations: gyro-stabilized mirror targeting; hard-disk-drive servo control and control of a piezoelectric actuator.

Robust and H-infinity Control can be used for graduate courses in robust control and as a reference for academic researchers; the reader should have completed first-year graduate courses in linear systems and multivariable control. It will also be of great value to engineers practising in the process, electronics and aerospace industries.

An unmanned aerial vehicle (UAV) is an aircraft that is equipped with necessary data processing units, sensors, automatic control and communications systems, and is capable of performing autonomously flight missions without a human pilot. Unmanned Rotorcraft Systems provides a complete treatment of the design of fully autonomous miniature rotorcraft UAVs. It is an integration of advanced technologies developed in communications, computing and control areas. In particular, it focuses on:

the systematic hardware construction;

software systems integration;

aerodynamic modeling; and

automatic flight control system design.

Emphasis is extended to the cooperative control and flight formation of multiple UAVs, and vision-based ground target tracking and landing on moving platforms. Other issues such as the development of GPSless indoor micro aerial vehicles and vision-based navigation are also highlighted.

The proposed monograph aims to explore the research and development of fully functional miniature UAV (unmanned-aerial-vehicle) rotorcraft. This consists of a small-scale basic rotorcraft with all necessary accessories onboard, and a ground station. The unmanned system is an integration of advanced technologies developed in communications, computing and control areas. It is an excellent testing ground for trialing and implementing modern control techniques. It is however a highly challenging process. The aerodynamics of a small-scale rotorcraft such as a hobby helicopter are similar to its full-scale counterpart but has some unique characteristics, such as the utilization of stabilizer bar and higher main/tail rotors rotation speed. Besides these, the strict limitation on payload also increases the difficulty on upgrading a small-scale rotorcraft to a UAV with full capacities. Based on its various characteristics and limitations, a light-weight but effective onboard computer system with corresponding onboard/ground software should be carefully designed to realize the system identification and automatic flight requirements. These issues will be addressed in detail in this monograph. Research on the following will be detailed:

utilizing the vision-based system for accomplishing ground target tracking;

attacking and landing;

cooperative control and flight formation of muitiple unmanned rotorcraft;

future research directions on the related areas.

The book will be a good reference for researchers and students working on the related subjects. Unmanned Rotorcraft Systems will be of great value to practicing engineers in rotorcraft industries and to researchers in areas related to the development of unmanned systems in general. It may be used as a reference for advanced undergraduate and graduate students in aeronautics and astrinautics, electrical and mechanical engineering."

This book presents a collection of papers from the International Symposium in Robotics Research (ISRR01). The goal of the symposium was to bring together active, leading robotics researchers from academia, government, and industry, to define the state of the art in robotics and its future direction.

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 is an edited collection by world-class experts, from diverse fields, focusing on integrating smart in-vehicle systems with human factors to enhance safety in automobiles. The book presents developments on road safety, in-vehicle technologies and state-of-the art systems. Includes coverage of DSP technologies in adaptive automobiles, algorithms and evaluation of in-car communication systems, driver-status monitoring and stress detection, in-vehicle dialogue systems and human-machine interfaces, challenges in video and audio processing for in-vehicle products, multi-sensor fusion for driver identification and vehicle to infrastructure wireless technologies.

This book presents the recently introduced and already widely referred semi-discretization method for the stability analysis of delayed dynamical systems. Delay differential equations often come up in different fields of engineering, like feedback control systems, machine tool vibrations, balancing/stabilization with reflex delay. The behavior of such systems is often counter-intuitive and closed form analytical formulas can rarely be given even for the linear stability conditions. If parametric excitation is coupled with the delay effect, then the governing equation is a delay differential equation with time periodic coefficients, and the stability properties are even more intriguing. The semi-discretization method is a simple but efficient method that is based on the discretization with respect to the delayed term and the periodic coefficients only. The method can effectively be used to construct stability diagrams in the space of system parameters.

This volume contains the Proceedings of the 3rd IFToMM Symposium on Mechanism Design for Robotics, held in Aalborg, Denmark, 2-4 June, 2015. The book contains papers on recent advances in the design of mechanisms and their robotic applications. It treats the following topics: mechanism design, mechanics of robots, parallel manipulators, actuators and their control, linkage and industrial manipulators, innovative mechanisms/robots and their applications, among others. The book can be used by researchers and engineers in the relevant areas of mechanisms, machines and robotics.

This book reveals that the way we perceive sex robots is how we perceive ourselves, overcoming the false human/non-human binary. From Greek myths, to the film Ex Machina, to Japanese technology, non-human sexuality has been at the heart of culture. In Sex Robots, the history of this culture is explored. This text sheds new light on what the sex robot represents and signifies, examining its philosophical implications within the context of today's society. This volume will be of interest to scholars of technology, cultural studies, the social sciences and philosophy.

This book provides an overview of the nonlinear model predictive control (NMPC) concept for application to innovative combustion engines. Readers can use this book to become more expert in advanced combustion engine control and to develop and implement their own NMPC algorithms to solve challenging control tasks in the field. The significance of the advantages and relevancy for practice is demonstrated by real-world engine and vehicle application examples. The author provides an overview of fundamental engine control systems, and addresses emerging control problems, showing how they can be solved with NMPC. The implementation of NMPC involves various development steps, including: * reduced-order modeling of the process; * analysis of system dynamics; * formulation of the optimization problem; and * real-time feasible numerical solution of the optimization problem. Readers will see the entire process of these steps, from the fundamentals to several innovative applications. The application examples highlight the actual difficulties and advantages when implementing NMPC for engine control applications. Nonlinear Model Predictive Control of Combustion Engines targets engineers and researchers in academia and industry working in the field of engine control. The book is laid out in a structured and easy-to-read manner, supported by code examples in MATLAB (R)/Simulink (R), thus expanding its readership to students and academics who would like to understand the fundamental concepts of NMPC. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

Building a robot that learns to perform a task has been acknowledged as one of the major challenges facing artificial intelligence. Self-improving robots would relieve humans from much of the drudgery of programming and would potentially allow operation in environments that were changeable or only partially known. Progress towards this goal would also make fundamental contributions to artificial intelligence by furthering our understanding of how to successfully integrate disparate abilities such as perception, planning, learning and action. Although its roots can be traced back to the late fifties, the area of robot learning has lately seen a resurgence of interest. The flurry of interest in robot learning has partly been fueled by exciting new work in the areas of reinforcement earning, behavior-based architectures, genetic algorithms, neural networks and the study of artificial life. Robot Learning gives an overview of some of the current research projects in robot learning being carried out at leading universities and research laboratories in the United States. The main research directions in robot learning covered in this book include: reinforcement learning, behavior-based architectures, neural networks, map learning, action models, navigation and guided exploration.

The fully automated estimation of the 6 degrees of freedom camera motion and the imaged 3D scenario using as the only input the pictures taken by the camera has been a long term aim in the computer vision community. The associated line of research has been known as Structure from Motion (SfM). An intense research effort during the latest decades has produced spectacular advances; the topic has reached a consistent state of maturity and most of its aspects are well known nowadays. 3D vision has immediate applications in many and diverse fields like robotics, videogames and augmented reality; and technological transfer is starting to be a reality. This book describes one of the first systems for sparse point-based 3D reconstruction and egomotion estimation from an image sequence; able to run in real-time at video frame rate and assuming quite weak prior knowledge about camera calibration, motion or scene. Its chapters unify the current perspectives of the robotics and computer vision communities on the 3D vision topic: As usual in robotics sensing, the explicit estimation and propagation of the uncertainty hold a central role in the sequential video processing and is shown to boost the efficiency and performance of the 3D estimation. On the other hand, some of the most relevant topics discussed in SfM by the computer vision scientists are addressed under this probabilistic filtering scheme; namely projective models, spurious rejection, model selection and self-calibration.