Master the principles of structural dynamics with this comprehensive and self-contained textbook, with key theoretical concepts explained through real-world engineering applications. The theory of natural modes of vibration, the finite element method and the dynamic response of structures is balanced with practical applications to give students a thorough contextual understanding of the subject. Enhanced coverage of damping, rotating systems, and parametric excitation provides students with superior understanding of these essential topics. Examples and homework problems, closely linked to real-world applications, enrich and deepen student understanding. Curated mathematical appendices equip students with all the tools necessary to excel, without disrupting coverage of core topics. Containing all the material needed for a one- or two-semester course, and accompanied online by Matlab code, this authoritative textbook is the ideal introduction for graduate students in aerospace, mechanical and civil engineering.

Ontologically Controlled Autonomous Systems: Principles, Operations and Architecture presents the main principles, operations and architecture involved in the design of a novel type of supervisory controller called an ontological controller. An ontological controller can be used to supervise any type of controller; however its intended applications are industrial-strength complex autonomous control systems using advanced programmable controllers. An ontological controller supervises a programmable controller in order to: Detect dynamically when the programmable controller is in a problematic control situation due to a violation of ontological assumptions and thus unable to achieve a pre-specified control goal (i.e. the identification operation), and When possible, move the programmable controller into such a state from which it can regain its control and eventually achieve the pre-specified control goal in spite of the previous violation of ontological assumptions (i.e. the recovery operation). Ontologically Controlled Autonomous Systems: Principles, Operations and Architecture presents for the first time a complete formal framework and results for ontological control. All results presented in the book originate from the practical industrial experience of the author. The intended readers for Ontologically Controlled Autonomous Systems: Principles, Operations and Architecture are professionals and students working in industrial control, discrete control, discrete-event systems, artificial intelligence, autonomous systems, programmable (logic) control design, robotics, real-time planning, safety-critical systems, Petri nets and PLC standards such as IEC1131.

Consisting of 23 refereed contributions, this volume offers a broad and diverse view of current research in control and estimation of partial differential equations. Topics addressed include, but are not limited to - control and stability of hyperbolic systems related to elasticity, linear and nonlinear; - control and identification of nonlinear parabolic systems; - exact and approximate controllability, and observability; - Pontryagin's maximum principle and dynamic programming in PDE; and - numerics pertinent to optimal and suboptimal control problems. This volume is primarily geared toward control theorists seeking information on the latest developments in their area of expertise. It may also serve as a stimulating reader to any researcher who wants to gain an impression of activities at the forefront of a vigorously expanding area in applied mathematics.

This book provides a detailed insight into Robotic Process Automation (RPA) technologies linked with AI that will help organizations implement Industry 4.0 procedures. RPA tools enhance their functionality by incorporating AI objectives, such as use of artificial neural network algorithms, text mining techniques, and natural language processing techniques for information extraction and the subsequent process of optimization and forecasting scenarios for the purpose of improving an organization's operational and business processes. The target readers of this book are researchers, professors, graduate students, scientists, policymakers, professionals, and developers working in the IT and ITeS sectors, i.e. people who are working on emerging technologies. This book also provides insights and decision support tools necessary for executives concerned with different industrial and organizational automation-centric jobs, knowledge dissemination, information, and policy development for automation in different educational, government, and non-government organizations. This book is of special interest to college and university educators who teach AI, machine learning, blockchain, business intelligence, cognitive intelligence, and brain intelligence courses in different capacities.

At the end of the nineteenth century Lyapunov and Poincare developed the so called qualitative theory of differential equations and introduced geometric- topological considerations which have led to the concept of dynamical systems. In its present abstract form this concept goes back to G.D. Birkhoff. This is also the starting point of Chapter 1 of this book in which uncontrolled and controlled time-continuous and time-discrete systems are investigated. Controlled dynamical systems could be considered as dynamical systems in the strong sense, if the controls were incorporated into the state space. We, however, adapt the conventional treatment of controlled systems as in control theory. We are mainly interested in the question of controllability of dynamical systems into equilibrium states. In the non-autonomous time-discrete case we also consider the problem of stabilization. We conclude with chaotic behavior of autonomous time discrete systems and actual real-world applications.

This book presents recent research work on stochastic jump hybrid systems. Specifically, the considered stochastic jump hybrid systems include Markovian jump Ito stochastic systems, Markovian jump linear-parameter-varying (LPV) systems, Markovian jump singular systems, Markovian jump two-dimensional (2-D) systems, and Markovian jump repeated scalar nonlinear systems. Some sufficient conditions are first established respectively for the stability and performances of those kinds of stochastic jump hybrid systems in terms of solution of linear matrix inequalities (LMIs). Based on the derived analysis conditions, the filtering and control problems are addressed. The book presents up-to-date research developments and novel methodologies on stochastic jump hybrid systems. The contents can be divided into two parts: the first part is focused on robust filter design problem, while the second part is put the emphasis on robust control problem. These methodologies provide a framework for stability and performance analysis, robust controller design, and robust filter design for the considered systems. Solutions to the design problems are presented in terms of LMIs. The book is a timely reflection of the developing area of filtering and control theories for Markovian jump hybrid systems with various kinds of imperfect information. It is a collection of a series of latest research results and therefore serves as a useful textbook for senior and/or graduate students who are interested in knowing 1) the state-of-the-art of linear filtering and control areas, and 2) recent advances in stochastic jump hybrid systems. The readers will also benefit from some new concepts, new models and new methodologies with practical significance in control engineering and signal processing.

This self-contained monograph describes basic set-theoretic methods for control. It provides a discussion of their links to fundamental problems in Lyapunov stability analysis and stabilization, optimal control, control under constraints, persistent disturbance rejection, and uncertain systems analysis and synthesis. The work presents several established and potentially new applications, along with numerical examples and case studies. A key theme is the trade-off between exact (but computationally intensive) and approximate (but conservative) solutions to problems. Mathematical language is kept to the minimum necessary.

This practical, student-focused text shows how to focus all of an organization's resources on continuous and simultaneous improvement of quality and productivity - thereby continually improving both performance and competitiveness. QUALITY MANAGEMENT FOR ORGANIZATIONAL EXCELLENCE: INTRODUCTION TO TOTAL QUALITY, 7/e coherently addresses all elements of quality management, including Lean, Six Sigma, Lean Six Sigma, and many topics that competitive books overlook (e.g., peak performance, partnering, manufacturing networks, culture, and crucial "people" aspects of quality). Direct and straightforward, it links "big picture" theories and principles to detailed real-world strategies and techniques. Throughout, critical thinking activities, discussion assignments, and research links promote deeper thinking and further exploration. This edition adds all-new cases, plus new information on topics ranging from supervision to certification, QFD and SPC to benchmarking and JIT.

Although the use of fuzzy control methods has grown nearly to the level of classical control, the true understanding of fuzzy control lags seriously behind. Moreover, most engineers are well versed in either traditional control or in fuzzy control-rarely both. Each has applications for which it is better suited, but without a good understanding of both, engineers cannot make a sound determination of which technique to use for a given situation.

A First Course in Fuzzy and Neural Control is designed to build the foundation needed to make those decisions. It begins with an introduction to standard control theory, then makes a smooth transition to complex problems that require innovative fuzzy, neural, and fuzzy-neural techniques. For each method, the authors clearly answer the questions: What is this new control method? Why is it needed? How is it implemented? Real-world examples, exercises, and ideas for student projects reinforce the concepts presented.

Developed from lecture notes for a highly successful course titled The Fundamentals of Soft Computing, the text is written in the same reader-friendly style as the authors' popular A First Course in Fuzzy Logic text. A First Course in Fuzzy and Neural Control requires only a basic background in mathematics and engineering and does not overwhelm students with unnecessary material but serves to motivate them toward more advanced studies.

This volume contains the Proceedings of the First International Congress for the Advancement of Mechanism, Machine, Robotics and Mechatronics Sciences (ICAMMRMS-2017), held in Beirut, Lebanon, October 2017. The book consists of twenty papers in six different fields covering multiple angles of machine and robotics sciences: mechanical design, control, structural synthesis, vibration study, and manufacturing. This volume is of interest to mechanical as well as electrical engineers.

This book makes the area of integration of renewable energy into the existing electricity grid accessible to engineers and researchers. This is a self-contained text which has models of power system devices and control theory necessary to understand and tune controllers in use currently. The new research in renewable energy integration is put into perspective by comparing the change in the system dynamics as compared to the traditional electricity grid. The emergence of the voltage stability problem is motivated by extensive examples. Various methods to mitigate this problem are discussed bringing out their merits clearly. As a solution to the voltage stability problem, the book covers the use of FACTS devices and basic control methods. An important contribution of this book is to introduce advanced control methods for voltage stability. It covers the application of output feedback methods with a special emphasis on how to bound modelling uncertainties and the use of robust control theory to design controllers for practical power systems. Special emphasis is given to designing controllers for FACTS devices to improve low-voltage ride-through capability of induction generators. As generally PV is connected in low voltage distribution area, this book also provides a systematic control design for the PV unit in distribution systems. The theory is amply illustrated with large IEEE Test systems with multiple generators and dynamic load. Controllers are designed using Matlab and tested using full system models in PSSE.

Research on humanoid robots has been mostly with the aim of developing robots that can replace humans in the performance of certain tasks. Motion planning for these robots can be quite difficult, due to their complex kinematics, dynamics and environment. It is consequently one of the key research topics in humanoid robotics research and the last few years have witnessed considerable progress in the field. Motion Planning for Humanoid Robots surveys the remarkable recent advancement in both the theoretical and the practical aspects of humanoid motion planning. Various motion planning frameworks are presented in Motion Planning for Humanoid Robots, including one for skill coordination and learning, and one for manipulating and grasping tasks. The problem of planning sequences of contacts that support acyclic motion in a highly constrained environment is addressed and a motion planner that enables a humanoid robot to push an object to a desired location on a cluttered table is described. The main areas of interest include: * whole body motion planning, * task planning, * biped gait planning, and * sensor feedback for motion planning. Torque-level control of multi-contact behavior, autonomous manipulation of moving obstacles, and movement control and planning architecture are also covered. Motion Planning for Humanoid Robots will help readers to understand the current research on humanoid motion planning. It is written for industrial engineers, advanced undergraduate and postgraduate students.

One of the most important methods in dealing with the optimization of large, complex systems is that of hierarchical decomposition. The idea is to reduce the overall complex problem into manageable approximate problems or subproblems, to solve these problems, and to construct a solution of the original problem from the solutions of these simpler prob lems. Development of such approaches for large complex systems has been identified as a particularly fruitful area by the Committee on the Next Decade in Operations Research (1988) [42] as well as by the Panel on Future Directions in Control Theory (1988) [65]. Most manufacturing firms are complex systems characterized by sev eral decision subsystems, such as finance, personnel, marketing, and op erations. They may have several plants and warehouses and a wide variety of machines and equipment devoted to producing a large number of different products. Moreover, they are subject to deterministic as well as stochastic discrete events, such as purchasing new equipment, hiring and layoff of personnel, and machine setups, failures, and repairs.

Mechatronics is a synergic discipline integrating precise mechanics, electrotechnics, electronics and IT technologies. The main goal of mechatronical approach to design of complex products is to achieve new quality of their utility value at reasonable price. Successful accomplishment of this task would not be possible without application of advanced software and hardware tools for simulation of design, technologies and production control and also for simulation of behavior of these products in order to provide the highest possible level of spatial and functional integration of the final product.

This book brings a review of the current state of the art in mechatronics, as presented at the 8th International Conference Mechatronics 2009, organized by the Brno Technical University, Faculty of Mechanical Engineering, Czech Republic. The specific topics of the conference are Modelling and Simulation, Metrology & Diagnostics, Sensorics & Photonics, Control & Robotics, MEMS Design & Mechatronic Products, Production Machines and Biomechanics. The selected contributions provide an insight into the current development of these scientific disciplines, present the new results of research and development and indicate the trends of development in the interdisciplinary field of mechatronic systems. Therefore, the book provides the latest and helpful information both for the R&D specialists and for the designers working in mechatronics and related fields.

This monograph presents and analyzes the optimization, game-theoretic and simulation models of control mechanisms for ecological-economic systems. It is devoted to integrated assessment mechanisms for total risks and losses, penalty mechanisms, risk payment mechanisms, financing and costs compensation mechanisms for risk level reduction, sales mechanisms for risk level quotas, audit mechanisms, mechanisms for expected losses reduction, economic motivation mechanisms, optimization mechanisms for regional environmental (risk level reduction) programs, and mechanisms for authorities' interests coordination. The book is aiming at undergraduate and postgraduate students, as well as at experts in mathematical modeling and control of ecological economic, socioeconomic and organizational systems.

Advances in H Control Theory is concerned with state-of-the-art developments in three areas: the extended treatment of mostly deterministic switched systems with dwell-time; the control of retarded stochastic state-multiplicative noisy systems; and a new approach to the control of biochemical systems, exemplified by the threonine synthesis and glycolytic pathways. Following an introduction and extensive literature survey, each of these major topics is the subject of an individual part of the book. The first two parts of the book contain several practical examples taken from various fields of control engineering including aircraft control, robot manipulation and process control. These examples are taken from the fields of deterministic switched systems and state-multiplicative noisy systems. The text is rounded out with short appendices covering mathematical fundamentals: -algebra and the input-output method for retarded systems. Advances in H Control Theory is written for engineers engaged in control systems research and development, for applied mathematicians interested in systems and control and for graduate students specializing in stochastic control.

This book presents a foray into the fascinating process of risk management, beginning from classical methods and approaches to understanding risk all the way into cutting-age thinking. Risk management by necessity must lie at the heart of governing our ever more complex digital societies. New phenomena and activities necessitate a new look at how individuals, firms, and states manage the uncertainty they must operate in. Initial chapters provide an introduction to traditional methods and show how they can be built upon to better understand the workings of the modern economy. Later chapters review digital activities and assets like cryptocurrencies showing how such emergent risks can be conceptualized better. Network theory figures prominently and the book demonstrates how it can be used to gauge the risk in the digital sectors of the economy. Predicting the unpredictable black swan events is also discussed in view of a wider adoption of economic simulations. The journey concludes by looking at how individuals perceive risk and make decisions as they operate in a virtual social network. This book interests the academic audience, but it also features insights and novel research results that are relevant for practitioners and policymakers.

This monograph focuses on characterizing the stability and performance consequences of inserting limited-capacity communication networks within a control loop. The text shows how integration of the ideas of control and estimation with those of communication and information theory can be used to provide important insights concerning several fundamental problems such as: * minimum data rate for stabilization of linear systems over noisy channels; * minimum network requirement for stabilization of linear systems over fading channels; and * stability of Kalman filtering with intermittent observations. A fundamental link is revealed between the topological entropy of linear dynamical systems and the capacities of communication channels. The design of a logarithmic quantizer for the stabilization of linear systems under various network environments is also extensively discussed and solutions to many problems of Kalman filtering with intermittent observations are demonstrated. Analysis and Design of Networked Control Systems will interest control theorists and engineers working with networked systems and may also be used as a resource for graduate students with backgrounds in applied mathematics, communications or control who are studying such systems.

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?"