This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. It presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including parametric interval uncertainties, iteration-domain frequency uncertainty, and iteration-domain stochastic uncertainty. The book shows how to use robust iterative learning control in the face of model uncertainty.

This volume describes new frontiers in medical and service robotics in the light of recent developments in technology to advance robot design and implementation. In particular, the work looks at advances in design, development and implementation of contemporary surgical, rehabilitation and biorobots. Surgical robots allow surgeons greater access to areas under operation using more precise and less invasive methods. Rehabilitation robots facilitate and support the lives of the infirm, elderly people, or those with dysfunction of body parts affecting movement. These robots are also used for rehabilitation and related procedures, such as training and therapy. Biorobots are designed to imitate the cognition of humans and animals. The need to substitute humans working on delicate, tiresome and monotonous tasks, or working with potentially health-damaging toxic materials, requires intelligent, high-performance service robots with the ability to cooperate, advanced communication and sophisticated perception and cognitive capabilities. Progress in this field is fast and results need to be disseminated to stimulate both practical applications and further research. Thus, these papers are a valuable addition to existing literature.

The human hand and its dexterity in grasping and manipulating objects are some of the hallmarks of the human species. For years, anatomic and biomechanical studies have deepened the understanding of the human hand's functioning and, in parallel, the robotics community has been working on the design of robotic hands capable of manipulating objects with a performance similar to that of the human hand. However, although many researchers have partially studied various aspects, to date there has been no comprehensive characterization of the human hand's function for grasping and manipulation of everyday life objects. This monograph explores the hypothesis that the confluence of both scientific fields, the biomechanical study of the human hand and the analysis of robotic manipulation of objects, would greatly benefit and advance both disciplines through simulation. Therefore, in this book, the current knowledge of robotics and biomechanics guides the design and implementation of a simulation framework focused on manipulation interactions that allows the study of the grasp through simulation. As a result, a valuable framework for the study of the grasp, with relevant applications in several fields such as robotics, biomechanics, ergonomics, rehabilitation and medicine, has been made available to these communities.

Stabilization, Optimal and Robust Control develops robust control of infinite-dimensional dynamical systems derived from time-dependent coupled PDEs associated with boundary-value problems. Rigorous analysis takes into account nonlinear system dynamics, evolutionary and coupled PDE behaviour and the selection of function spaces in terms of solvability and model quality.

Mathematical foundations are provided so that the book remains accessible to the non-control-specialist. Following chapters giving a general view of convex analysis and optimization and robust and optimal control, problems arising in fluid mechanical, biological and materials scientific systems are laid out in detail.

The combination of mathematical fundamentals with application of current interest will make this book of much interest to researchers and graduate students looking at complex problems in mathematics, physics and biology as well as to control theorists.

This monograph presents a wider spectrum of researches, developments, and case specific studies in the area of smart power systems and integration of renewable energy systems. The book will be for the benefit of a wider audience including researchers, postgraduate students, practicing engineers, academics, and regulatory policy makers. It covers a wide range of topics from fundamentals, and modelling and simulation aspects of traditional and smart power systems to grid integration of renewables; Micro Grids; challenges in planning and operation of a smart power system; risks, security, and stability in smart operation of a power system; and applied research in energy storage.

Nowadays, multiple attention have been paid on a robot working in the human living environment, such as in the field of medical, welfare, entertainment and so on. Various types of researches are being conducted actively in a variety of fields such as artificial intelligence, cognitive engineering, sensor- technology, interfaces and motion control. In the future, it is expected to realize super high functional human-like robot by integrating technologies in various fields including these types of researches. The book represents new developments and advances in the field of bio-inspired robotics research introducing the state of the art, the idea of multi-locomotion robotic system to implement the diversity of animal motion. It covers theoretical and computational aspects of Passive Dynamic Autonomous Control (PDAC), robot motion control, multi legged walking and climbing as well as brachiation focusing concrete robot systems, components and applications. In addition, gorilla type robot systems are described as hardware of Multi-Locomotion Robotic system. It is useful for students and researchers in the field of robotics in general, bio-inspired robots, multi-modal locomotion, legged walking, motion control, and humanoid robots. Furthermore, it is also of interest for lecturers and engineers in practice building systems cooperating with humans.

The idea of optimization runs through most parts of control theory. The simplest optimal controls are preplanned (programmed) ones. The problem of constructing optimal preplanned controls has been extensively worked out in literature (see, e. g., the Pontrjagin maximum principle giving necessary conditions of preplanned control optimality). However, the concept of op timality itself has a restrictive character: it is limited by what one means under optimality in each separate case. The internal contradictoriness of the preplanned control optimality ("the better is the enemy of the good") yields that the practical significance of optimal preplanned controls proves to be not great: such controls are usually sensitive to unregistered disturbances (includ ing the round-off errors which are inevitable when computer devices are used for forming controls), as there is the effect of disturbance accumulation in the control process which makes controls to be of little use on large time inter vals. This gap is mainly provoked by oversimplified settings of optimization problems. The outstanding result of control theory established in the end of the first half of our century is that controls in feedback form ensure the weak sensitivity of closed loop systems with respect to "small" unregistered internal and external disturbances acting in them (here we do not need to discuss performance indexes, since the considered phenomenon is of general nature). But by far not all optimal preplanned controls can be represented in a feedback form."

This textbook aims to provide a clear understanding of the various tools of analysis and design for robust stability and performance of uncertain dynamic systems. In model-based control design and analysis, mathematical models can never completely represent the "real world" system that is being modeled, and thus it is imperative to incorporate and accommodate a level of uncertainty into the models. This book directly addresses these issues from a deterministic uncertainty viewpoint and focuses on the interval parameter characterization of uncertain systems. Various tools of analysis and design are presented in a consolidated manner. This volume fills a current gap in published works by explicitly addressing the subject of control of dynamic systems from linear state space framework, namely using a time-domain, matrix-theory based approach. This book also: Presents and formulates the robustness problem in a linear state space model framework. Illustrates various systems level methodologies with examples and applications drawn from aerospace, electrical and mechanical engineering. Provides connections between lyapunov-based matrix approach and the transfer function based polynomial approaches. Robust Control of Uncertain Dynamic Systems: A Linear State Space Approach is an ideal book for first year graduate students taking a course in robust control in aerospace, mechanical, or electrical engineering.

This book deals with the class of singular systems with random abrupt changes also known as singular Markovian jump systems. Various problems and their robustness are tackled. The book examines both the theoretical and practical aspects of the control problems from the angle of the structural properties of linear systems. It can be used as a textbook as well as a reference for researchers in control or mathematics with interest in control theory.

This book presents the concept of cognition in a clear, lucid and highly comprehensive style. It provides an in-depth analysis of mathematical models and algorithms, and demonstrates their application with real life experiments.

This book presents research on informational and mathematical aspects of networked sensing systems. It brings together internationally reputed researchers from different communities, focused on the common theme of distributed sensing, inferencing, and control over networks. The timeliness of the book is evidenced by the explosion of several independent special sessions devoted to specific aspects of sensor networks in reputed international conferences.

This monograph presents design methodologies for (robust) fractional control systems. It shows the reader how to take advantage of the superior flexibility of fractional control systems compared with integer-order systems in achieving more challenging control requirements. There is a high degree of current interest in fractional systems and fractional control arising from both academia and industry and readers from both milieux are catered to in the text. Different design approaches having in common a trade-off between robustness and performance of the control system are considered explicitly. The text generalizes methodologies, techniques and theoretical results that have been successfully applied in classical (integer) control to the fractional case. The first part of Advances in Robust Fractional Control is the more industrially oriented. It focuses on the design of fractional controllers for integer processes. In particular, it considers fractional-order proportional-integral-derivative controllers, because integer-order PID regulators are, undoubtedly, the controllers most frequently adopted in industry. The second part of the book deals with a more general approach to fractional control systems, extending techniques (such as H-infinity optimal control and optimal input-output inversion based control) originally devised for classical integer-order control. Advances in Robust Fractional Control will be a useful reference for the large number of academic researchers in fractional control, for their industrial counterparts and for graduate students who want to learn more about this subject.

This book presents the latest results on predictive control of networked systems, where communication constraints (e.g., network-induced delays and packet dropouts) and cyber attacks (e.g., deception attacks and denial-of-service attacks) are considered. For the former, it proposes several networked predictive control (NPC) methods based on input-output models and state-space models respectively. For the latter, it designs secure NPC schemes from the perspectives of information security and real-time control. Furthermore, it uses practical experiments to demonstrate the effectiveness and applicability of all the methods, bridging the gap between control theory and practical applications. The book is of interest to academic researchers, R&D engineers, and graduate students in control engineering, networked control systems and cyber-physical systems.

The research book is focused on the recent advances in computer vision methodologies and innovations in practice. The Contributions include: * Human Action Recognition: Contour-Based and Silhouette-based Approaches. * The Application of Machine Learning Techniques to Real Time Audience Analysis System. * Panorama Construction from Multi-view Cameras in Outdoor Scenes. * A New Real-Time Method of Contextual Image Description and Its Application in Robot Navigation and Intelligent Control. * Perception of Audio Visual Information for Mobile Robot Motion Control Systems. * Adaptive Surveillance Algorithms Based on the Situation Analysis. * Enhanced, Synthetic and Combined Vision Technologies for Civil Aviation. * Navigation of Autonomous Underwater Vehicles Using Acoustic and Visual Data Processing. * Efficient Denoising Algorithms for Intelligent Recognition Systems. * Image Segmentation Based on Two-dimensional Markov Chains. The book is directed to the PhD students, professors, researchers and software developers working in the areas of digital video processing and computer vision technologies.

Digital Twins for Healthcare: Design, Challenges and Solutions establishes the state-of-art in the specification, design, creation, deployment and exploitation of digital twins' technologies for healthcare and wellbeing. A digital twin is a digital replication of a living or non-living physical entity. When data is transmitted seamlessly, it bridges the physical and virtual worlds, thus allowing the virtual entity to exist simultaneously with the physical entity. A digital twin facilitates the means to understand, monitor, and optimize the functions of the physical entity and provide continuous feedback. It can be used to improve citizens' quality of life and wellbeing in smart cities and the virtualization of industrial processes.

This book presents the most recent advances in the research and applications of reconfigurable mechanisms and robots. It collects 93 independently reviewed papers presented at the Third ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots (ReMAR 2015) held in Beijing, China, 20-22 July 2015. The conference papers are organized into seven parts to cover the reconfiguration theory, topology, kinematics and design of reconfigurable mechanisms including reconfigurable parallel mechanisms. The most recent results on reconfigurable robots are presented including their analysis, design, simulation and control. Bio-inspired mechanisms are also explored in the challenging fields of rehabilitation and minimally invasive surgery. This book further addresses deployable mechanisms and origami-inspired mechanisms and showcases a wide range of successful applications of reconfigurable mechanisms and robots. Advances in Reconfigurable Mechanisms and Robots II should be of interest for researchers, engineers and postgraduate students in mechanical engineering, electrical engineering, computer science and mathematics.

This book collects the latest theoretical and technological concepts in the design and control of various linear machines and drive systems. Discussing advances in the new linear machine topologies, integrated modeling, multi-objective optimization techniques, and high-performance control strategies, it focuses on emerging applications of linear machines in transportation and energy systems. The book presents both theoretical and practical/experimental results, providing a consistent compilation of fundamental theories, a compendium of current research and development activities as well as new directions to overcome critical limitations.

A mobile agent is a software program with the capability to suspend its execution and resume it on another computer. Agents are a relatively recent development in computer science, which have become a popular and useful methodology for the modelling and implementation of distributed systems, particularly those consisting of a number of largely autonomous components. The extensive use of multi-agent systems in various areas including information management, industrial control and manufacturing systems, suggests that the multi-agent systems methodology may also be appropriate for the design of power system automation systems.

IP Network-based Multi-agent Systems for Industrial Automation: Information Management, Condition Monitoring and Control of Power Systems is the first book to present an introduction to the use of the Internet protocol suite and multi-agent systems for the information management, online monitoring and control of distributed power system substations. It proposes an open architecture for information management and control, based on the concepts of multi-agent systems and mobile agents. In this book, mobile agents are applied to the retrieval and analysis of substation data, and to remote operator intervention. This book also describes a prototype implementation of the architecture, in the form of a substation information management system, which has been demonstrated and evaluated using a substation simulator. The architecture is also evaluated theoretically with respect to its performance, modifiability, functionality and reliability.

As mobile agent technologies are in the early stages the real applications of these technologies are rare; IPNetwork-based Multi-agent Systems for Industrial Automation: Information Management, Condition Monitoring and Control of Power Systems will be an excellent reference for postgraduates, researchers and academics in engineering and computer science, as well as engineers in system automation and managers in distributed industrial systems.

This volume surveys three decades of modern robot control theory and describes how the work of Suguru Arimoto shaped its development. Twelve survey articles written by experts associated with Suguru Arimoto at various stages in his career treat the subject comprehensively. This book provides an important reference for graduate students and researchers, as well as for mathematicians, engineers and scientists whose work involves robot control theory.

In 1960, R. E. Kalman published his celebrated paper on recursive min imum variance estimation in dynamical systems [14]. This paper, which introduced an algorithm that has since been known as the discrete Kalman filter, produced a virtual revolution in the field of systems engineering. Today, Kalman filters are used in such diverse areas as navigation, guid ance, oil drilling, water and air quality, and geodetic surveys. In addition, Kalman's work led to a multitude of books and papers on minimum vari ance estimation in dynamical systems, including one by Kalman and Bucy on continuous time systems [15]. Most of this work was done outside of the mathematics and statistics communities and, in the spirit of true academic parochialism, was, with a few notable exceptions, ignored by them. This text is my effort toward closing that chasm. For mathematics students, the Kalman filtering theorem is a beautiful illustration of functional analysis in action; Hilbert spaces being used to solve an extremely important problem in applied mathematics. For statistics students, the Kalman filter is a vivid example of Bayesian statistics in action. The present text grew out of a series of graduate courses given by me in the past decade. Most of these courses were given at the University of Mas sachusetts at Amherst.

This book reviews the fundamentals of screw theory concerned with velocity analysis of rigid-bodies, confirmed with detailed and explicit proofs. The author additionally investigates acceleration, jerk, and hyper-jerk analyses of rigid-bodies following the trend of the velocity analysis. With the material provided in this book, readers can extend the theory of screws into the kinematics of optional order of rigid-bodies. Illustrative examples and exercises to reinforce learning are provided. Of particular note, the kinematics of emblematic parallel manipulators, such as the Delta robot as well as the original Gough and Stewart platforms are revisited applying, in addition to the theory of screws, new methods devoted to simplify the corresponding forward-displacement analysis, a challenging task for most parallel manipulators.

Verification presents the most time-consuming task in the integrated circuit design process. The increasing similarity between implementation verification and the ever-needed task of providing vectors for manufacturing fault testing is tempting many professionals to combine verification and testing efforts.
This book presents the basis for reusing the test vector generation and simulation for the purpose of implementation verification, to result in a significant timesaving. The book brings the results in the direction of merging manufacturing test vector generation and verification. It first discusses error fault models suitable for approaching the verification by testing methods. Then, it elaborates a proposal for an implicit fault model that uses the Arithmetic Transform representation of a circuit and the faults. Presented is the fundamental link between the error size and the test vector size, which allows parametrizable verification by test vectors. Furthermore, the test vector set is sufficient not only for detecting, but also for diagnosing and correcting the design errors.
The practical use of any such simulation-based verification scheme can be seriously impaired by redundant faults, that otherwise require exhaustive simulations. The redundant fault identification methods are presented that are well suited for the type of faults considered. Finally, the same representation can be used to augment and expand the formal verification schemes that are to be used in conjunction with the simulation-based verification.
The primary audience for Verification by Error Modeling includes researchers in verification and testing, managers in charge of verification of test andpracticing engineers. Due to its comprehensive coverage of background topics, the book can also be used for teaching courses on verification and test topics.

This book reports on the latest findings in the application of the wide area measurement systems (WAMS) in the analysis and control of power systems. The book collects new research ideas and achievements including a delay-dependent robust design method, a wide area robust coordination strategy, a hybrid assessment and choice method for wide area signals, a free-weighting matrices method and its application, as well as the online identification methods for low-frequency oscillations. The main original research results of this book are a comprehensive summary of the authors' latest six-year study. The book will be of interest to academic researchers, R&D engineers and graduate students in power systems who wish to learn the core principles, methods, algorithms, and applications of the WAMS.

The interest in control of nonlinear partial differential equation (PDE) sys tems has been triggered by the need to achieve tight distributed control of transport-reaction processes that exhibit highly nonlinear behavior and strong spatial variations. Drawing from recent advances in dynamics of PDE systems and nonlinear control theory, control of nonlinear PDEs has evolved into a very active research area of systems and control. This book the first of its kind- presents general methods for the synthesis of nonlinear and robust feedback controllers for broad classes of nonlinear PDE sys tems and illustrates their applications to transport-reaction processes of industrial interest. Specifically, our attention focuses on quasi-linear hyperbolic and parabolic PDE systems for which the manipulated inputs and measured and controlled outputs are distributed in space and bounded. We use geometric and Lyapunov-based control techniques to synthesize nonlinear and robust controllers that use a finite number of measurement sensors and control actuators to achieve stabilization of the closed-loop system, output track ing, and attenuation of the effect of model uncertainty. The controllers are successfully applied to numerous convection-reaction and diffusion-reaction processes, including a rapid thermal chemical vapor deposition reactor and a Czochralski crystal growth process. The book includes comparisons of the proposed nonlinear and robust control methods with other approaches and discussions of practical implementation issues."