Presents a number of new and potentially useful self-learning (adaptive) control algorithms and theoretical as well as practical results for both unconstrained and constrained finite Markov chains-efficiently processing new information by adjusting the control strategies directly or indirectly.

This up-to-the-minute reference/text provides vital information on new approaches to stability, stabilization, control design, and filtering of electronics and computer systems-explicating the latest developments in time-delay systems (TDS) and uncertain time-delay systems (UTDS). Features helpful appendices detailing important facets of matrix theory, standard lemmas and mathematical results, and applications of industry-tested software Utilizing mathematical formality to foster intuitive understanding, Robust Control and Filtering for Time-Delay Systems discusses finite capabilities of data processing and transmission throughout systems analyzes inherent physical phenomena and computational delays impacting system performance showcases the state-space approach in systems representation and analysis defines and delineates concepts of robustness, robust performance, and robust design highlights linear and many classes of nonlinear system theory, matrix theory, and modern control theory describes delays as constant or time-varying, known or unknown, deterministic or stochastic assesses continuous-time and discrete-time systems independently and in relation to each other elucidates stability analysis and control synthesis supplies unification of results on control design and filtering and more Containing over 300 bibliographic citations and more than 1500 equations, Robust Control and Filtering for Time-Delay Systems is a must-read reference for electrical, electronics, computer, and control engineers, and an exceptional text for upper-level undergraduate and graduate students in these disciplines.

Production costs are being reduced by automation, robotics, computer-integrated manufacturing, cost reduction studies and more. These new technologies are expensive to buy, repair, and maintain. Hence, the demand on maintenance is growing and its costs are escalating. This new environment is compelling industrial maintenance organizations to make the transition from fixing broken machines to higher-level business units for securing production capacity. On the academic front, research in the area of maintenance management and engineering is receiving tremendous interest from researchers. Many papers have appeared in the literature dealing with the modeling and solution of maintenance problems using operations research (OR) and management science (MS) techniques. This area represents an opportunity for making significant contributions by the OR and MS communities. Maintenance, Modeling, and Optimization provides in one volume the latest developments in the area of maintenance modeling. Prominent scholars have contributed chapters covering a wide range of topics. We hope that this initial contribution will serve as a useful informative introduction to this field that may permit additional developments and useful directions for more research in this fast-growing area. The book is divided into six parts and contains seventeen chapters. Each chapter has been subject to review by at least two experts in the area of maintenance modeling and optimization. The first chapter provides an introduction to major maintenance modeling areas illustrated with some basic models. Part II contains five chapters dealing with maintenance planning and scheduling. Part III deals with preventive maintenance in six chapters. Part IV focuses on condition-based maintenance and contains two chapters. Part V deals with integrated production and maintenance models and contains two chapters. Part VI addresses issues related to maintenance and new technologies, and also deals with Just-in-Time (JIT) and Maintenance.

Quantitative Feedback Design of Linear and Nonlinear Control Systems is a self-contained book dealing with the theory and practice of Quantitative Feedback Theory (QFT). The author presents feedback synthesis techniques for single-input single-output, multi-input multi-output linear time-invariant and nonlinear plants based on the QFT method. Included are design details and graphs which do not appear in the literature, which will enable engineers and researchers to understand QFT in greater depth. Engineers will be able to apply QFT and the design techniques to many applications, such as flight and chemical plant control, robotics, space, vehicle and military industries, and numerous other uses. All of the examples were implemented using MatlabA(R) Version 5.3; the script file can be found at the author's Web site. QFT results in efficient designs because it synthesizes a controller for the exact amount of plant uncertainty, disturbances and required specifications. Quantitative Feedback Design of Linear and Nonlinear Control Systems is a pioneering work that illuminates QFT, making the theory - and practice - come alive.

This book is intended to be an exhaustive study on regularity and other properties of continuity for different types of non-additive multimeasures and with respect to different types of topologies. The book is addressed to graduate and postgraduate students, teachers and all researchers in mathematics, but not only. Since the notions and results offered by this book are closely related to various notions of the theory of probability, this book will be useful to a wider category of readers, using multivalued analysis techniques in areas such as control theory and optimization, economic mathematics, game theory, decision theory, etc. Measure and integration theory developed during the early years of the 20th century is one of the most important contributions to modern mathematical analysis, with important applications in many fields. In the last years, many classical problems from measure theory have been treated in the non-additive case and also extended in the set-valued case. The property of regularity is involved in many results of mathematical analysis, due to its applications in probability theory, stochastic processes, optimal control problems, dynamical systems, Markov chains, potential theory etc.

The contributions for this book have been gathered over several years from conferences held in the series of Mechatronics and Machine Vision in Practice, the latest of which was held in Ankara, Turkey. The essential aspect is that they concern practical applications rather than the derivation of mere theory, though simulations and visualization are important components. The topics range from mining, with its heavy engineering, to the delicate machining of holes in the human skull or robots for surgery on human flesh. Mobile robots continue to be a hot topic, both from the need for navigation and for the task of stabilization of unmanned aerial vehicles. The swinging of a spray rig is damped, while machine vision is used for the control of heating in an asphalt-laying machine. Manipulators are featured, both for general tasks and in the form of grasping fingers. A robot arm is proposed for adding to the mobility scooter of the elderly. Can EEG signals be a means to control a robot? Can face recognition be achieved in varying illumination?"

Hidenori Kimura, renowned system and control theorist, turned 60 years of age in November, 2001. To celebrate this memorable occasion, his friends, collaborators, and former students gathered from all over the world and held a symposium in his honor on November 1 and 2, 2001, at the Sanjo Conference Hall at the University of Tokyo. Reflecting his current research interests, the symposium was entitled "Cybernetics in the 21st Century: Information and Complexity in Control Theory," and it drew nearly 150 attendees. There were twenty-five lectures, on which the present volume is based. Hidenori Kimura was born on November 3, 1941, in Tokyo, just prior to the outbreak of the Second World War. It is not hard to imagine, then, that his early days, like those of so many of his contemporaries, must have been difficult. Fortunately, the war ended in 1945, and his generation found itself thoroughly occupied with the rebuilding effort and with Japan's uphill journey in the last half-century. He entered the University of Tokyo in 1963, received a B. S. in 1965, an M. S. in 1967, and, in 1970, a Ph. D. degree for his dissertation "A Study of Differential Games. " After obtaining his doctorate, he joined the Department of Control En gineering at Osaka University as a research associate, and in 1973 he was promoted to an associate professor."

This book focusses on Industry 4.0 which is one of the most challenging trends for all categories of manufacturing enterprises. In this book, variety of mechatronic solutions are discussed to develop a manufacturing control system for small and medium-sized enterprises as they impose to improve their capabilities by integration into Industry 4.0 standards.

This monograph focuses on how to achieve more robot autonomy by means of reliable processing skills. "Nonlinear Kalman Filtering for Force-Controlled Robot Tasks " discusses the latest developments in the areas of contact modeling, nonlinear parameter estimation and task plan optimization for improved estimation accuracy. Kalman filtering techniques are applied to identify the contact state based on force sensing between a grasped object and the environment. The potential of this work is to be found not only for industrial robot operation in space, sub-sea or nuclear scenarios, but also for service robots operating in unstructured environments co-habited by humans where autonomous compliant tasks require active sensing.

Distributed manipulation effects motion on objects through a large number of points of contact. The primary benefit of distributed manipulators is that many small inexpensive mechanisms can move and transport large heavy objects. In fact, each individual component is simple, but their combined effect is quite powerful. Furthermore, distributed manipulators are fault-tolerant because if one component breaks, the other components can compensate for the failure and the whole system can still perform its task. Finally, distributed manipulators can perform a variety of tasks in parallel. Distributed manipulation can be performed by many types of mechanisms at different scales. Due to the recent advances of MEMS (micro-electro-mechanical system) technology, it has become feasible to quickly manufacture distributed micro-manipulators at low cost. One such system is an actuator array where hundreds of micro-scaled actuators transport and manipulate small objects that rest on them. Macroscopic versions of the actuator array have also been developed and analyzed. Another form of distributed manipulation is derived from a vibrating plate, and teams of mobile robots have been used to herd large objects into desired locations. There are many fundamental issues involved in distributed manipulation. Since a distributed manipulator has many actuators, distributed control strategies must be considered to effectively manipulate objects. A basic understanding of contact analysis between the actuators and object must also be considered. When each actuator in the array has a sensor, distributed sensing presents some basic research challenges. Distributed computation and communication are key issues to enable the successful deployment of distributed manipulators into use. Finally, the trade-off in centralized and de-centralized approaches in all of these algorithms must be investigated.

The objective of this dissertation is to advance the state-of-the-art in the kinematic modeling, identification, and control of robotic manipulators with rigid links in an effort to improve robot kinematic performance. The positioning accuracy of commercially-available industrial robotic manipulators depends upon a kinematic model which describes the robot geometry in a parametric form. Manufacturing error in the machining and assembly of manipulators lead to discrepancies between the design parameters and the physical structure. Improving the kinematic perfor mance thus requires the identification of the actual kinematic parameters of each individual robot. The identified kinematic parameters are referred to as the arm signature. Existing robot kinematic models, such as the Denavit-Hartenberg model, are not directly applicable to kinematic parameter identification. In this dissertation we introduce a new kinematic model, called the 5-Model, which is applicable to kinematic parameter identification, and use it as the foundation for our development of a general technique for identifying the kinematic parameters of any robot with rigid links."

The structural optimization procedure presented in this book makes it possible to achieve seismic protection through integrated structural/control system design. In particular, it is explained how slender structural systems with a high seismic performance can be achieved through inclusion of viscous and viscoelastic dampers as an integral part of the system. Readers are provided with essential introductory information on passive structural control and passive energy dissipation systems. Dynamic analyses of both single and multiple degree of freedom systems are performed in order to verify the achievement of pre-assigned performance targets, and it is explained how the optimal integrated design methodology, also relevant to retrofitting of existing buildings, should be applied. The book illustrates how structural control research is opening up new possibilities in structural forms and configurations without compromising structural performance.

This book presents a foundation for a broad class of mobile robot mapping and navigation methodologies for indoor, outdoor, and exploratory missions. It addresses the challenging problem of autonomous navigation in dynamic environments, presenting new ideas and approaches in this emerging technical domain. Coverage discusses in detail various related challenging technical aspects and addresses upcoming technologies in this field.

As design complexity in chips and devices continues to rise, so, too, does the demand for functional verification. Principles of Functional Verification is a hands-on, practical text that will help train professionals in the field of engineering on the methodology and approaches to verification.
In practice, the architectural intent of a device is necessarily abstract. The implementation process, however, must define the detailed mechanisms to achieve the architectural goals. Based on a decade of experience, Principles of Functional Verification intends to pinpoint the issues, provide strategies to solve the issues, and present practical applications for narrowing the gap between architectural intent and implementation.
The book is divided into three parts, each building upon the chapters within the previous part. Part One addresses why functional verification is necessary, its definition and goals. In Part Two, the heart of the methodology and approaches to solving verification issues are examined. Each chapter in this part ends with exercises to apply what was discussed in the chapter. Part Three looks at practical applications, discussing project planning, resource requirements, and costs. Each chapter throughout all three parts will open with Key Objectives, focal points the reader can expect to review in the chapter.

* Takes a "holistic" approach to verification issues
* Approach is not restricted to one language
* Discussed the verification process, not just how to use the verification language

Predictive control is a powerful tool in dealing with those processes with large time delays. Generalized Predictive Control (GPC) is the most popular approach to the subject, and this text discusses the application of GPC starting with the concept of long-range predictive control and its need in medicine (particularly automated drug deliveries). The concept of adaptation is also emphasized with respect to patient-to-patient parameter variations. Subsequent chapters discuss interactions, comparisons and various aspects of GPC. The book concludes by putting into perpective the generic nature of the architecture built around GPC and which provides model-based fault diagnosis with control.

This book provides robust analysis and synthesis tools for Markovian jump systems in the finite-time domain with specified performances. It explores how these tools can make the systems more applicable to fields such as economic systems, ecological systems and solar thermal central receivers, by limiting system trajectories in the desired bound in a given time interval. Robust Control for Discrete-Time Markovian Jump Systems in the Finite-Time Domain focuses on multiple aspects of finite-time stability and control, including: finite-time H-infinity control; finite-time sliding mode control; finite-time multi-frequency control; finite-time model predictive control; and high-order moment finite-time control for multi-mode systems and also provides many methods and algorithms to solve problems related to Markovian jump systems with simulation examples that illustrate the design procedure and confirm the results of the methods proposed. The thorough discussion of these topics makes the book a useful guide for researchers, industrial engineers and graduate students alike, enabling them systematically to establish the modeling, analysis and synthesis for Markovian jump systems in the finite-time domain.

Actuator saturation is probably the most frequent nonlinearity encountered in control applications. Input saturation leads to controller windup, removable by structural modification during compensator realization and plant windup which calls for additional dynamics.

Peter Hippe presents solutions to the windup prevention problem for stable and unstable single-input-single-output and multiple-input-multiple-output (MIMO) systems. The solutions use only standard tools for the investigation of linear systems a" state equations, transfer functions, etc. The stability tests are based on well-known criteria for loops consisting of a linear part with isolated sector-type nonlinearity. Less rigorous "engineering solutions" which guarantee improved performance but without strict proof of stability are also demonstrated.

MIMO systems in which the behaviour of controlled variables is decoupled require specific input vectors and so also suffer problems of directionality when their input signals saturate. This can have extremely deleterious consequences for closed-loop behaviour. Windup in Control offers an exact solution to this directionality problem for stable and unstable systems. The methods laid out in this survey also integrate solutions for applications with rate-constrained actuators and for bumpless transfer from manual to automatic during system start-up or in override control. Developments in control methods are always supplemented by easily repeated numerical examples.

Academics doing control-related research in electronics, mechanics, or mechatronics and engineers working in the process industries will find this book an extremely useful overview of systematic windupprevention for all kinds of systems. It also has valuable insights to offer the graduate student of control.

- the book provides a short and accessible introduction to AI for learners - it examines seven different educational roles and settings, from AI as a peer to AI as a tutor and AI as textbook, among others - it considers both opportunities and risks: technological developments as well as ethical considerations

This book reports on the latest advances in the study of Networked Control Systems (NCSs). It highlights novel research concepts on NCSs; the analysis and synthesis of NCSs with special attention to their networked character; self- and event-triggered communication schemes for conserving limited network resources; and communication and control co-design for improving the efficiency of NCSs. The book will be of interest to university researchers, control and network engineers, and graduate students in the control engineering, communication and network sciences interested in learning the core principles, methods, algorithms and applications of NCSs.

This book includes significant recent research on robotic algorithms. It has been written by leading experts in the field. The 15th Workshop on the Algorithmic Foundations of Robotics (WAFR) was held on June 22-24, 2022, at the University of Maryland, College Park, Maryland. Each chapter represents an exciting state-of-the-art development in robotic algorithms that was presented at this 15th incarnation of WAFR. Different chapters combine ideas from a wide variety of fields, spanning and combining planning (for tasks, paths, motion, navigation, coverage, and patrol), computational geometry and topology, control theory, machine learning, formal methods, game theory, information theory, and theoretical computer science. Many of these papers explore new and interesting problems and problem variants that include human-robot interaction, planning and reasoning under uncertainty, dynamic environments, distributed decision making, multi-agent coordination, and heterogeneity.

This book introduces a family of large-signal stability-based control methods for different power inverters (grid-connected inverter, standalone inverter, single-phase inverter, and three-phase inverter) in practical applications. Power inverters have stability issues, which include the inverter's own instability as well as the inverter's instability in relation to the other power electronic devices in the system (i.e., weak grid and the EMI filter). Most of the stability analyses and solutions are based on small-signal stability technology. Unfortunately, in actuality, the majority of practical instability concerns in power inverter systems are large-signal stability problems, which, when compared to small-signal stability problems, can cause substantial damage to electrical equipment. As a result, researchers must conduct a comprehensive investigation of the large-signal stability challenge and solutions for power inverters. This book can be used as a reference for researchers, power inverters manufacturers, and end-users. As a result, the book will not become obsolete in the near future, regardless of technology advancements.

This book focuses on green computing-based network security techniques and addresses the challenges involved in practical implementation. It also explores the idea of energy-efficient computing for network and data security and covers the security threats involved in social networks, data centers, IoT, and biomedical applications. Green Computing in Network Security: Energy Efficient Solutions for Business and Home includes analysis of green-security mechanisms and explores the role of green computing for secured modern internet applications. It discusses green computing-based distributed learning approaches for security and emphasizes the development of green computing-based security systems for IoT devices. Written with researchers, academic libraries, and professionals in mind so they can get up to speed on network security, the challenges, and implementation processes.

This second edition of Precision Motion Control focuses on enabling technologies for precision engineering. It has been extensively edited and rewritten throughout with the following particular areas being expanded or added: * piezoelectric actuators * fine movement control * gantry-stage control * interpolation of quadrature encoder signals * geometrical error modeling for single-, dual- and general-XY-axis stages.

In the research area of computer science, practitioners are constantly searching for faster platforms with pertinent results. With analytics that span environmental development to computer hardware emulation, problem-solving algorithms are in high demand. Field-Programmable Gate Array (FPGA) is a promising computing platform that can be significantly faster for some applications and can be applied to a variety of fields. FPGA Algorithms and Applications in the IoT, AI, and High-Performance Computing provides emerging research exploring the theoretical and practical aspects of computable algorithms and applications within robotics and electronics development. Featuring coverage on a broad range of topics such as neuroscience, bioinformatics, and artificial intelligence, this book is ideally designed for computer science specialists, researchers, professors, and students seeking current research on cognitive analytics and advanced computing.

Much work on analysis and synthesis problems relating to the multiple model approach has already been undertaken. This has been motivated by the desire to establish the problems of control law synthesis and full state estimation in numerical terms.In recent years, a general approach based on multiple LTI models (linear or affine) around various function points has been proposed. This so-called multiple model approach is a convex polytopic representation, which can be obtained either directly from a nonlinear mathematical model, through mathematical transformation or through linearization around various function points.This book concentrates on the analysis of the stability and synthesis of control laws and observations for multiple models. The authors' approach is essentially based on Lyapunov's second method and LMI formulation. Uncertain multiple models with unknown inputs are studied and quadratic and non-quadratic Lyapunov functions are also considered.