The physical processes which initiate and maintain motion have been a major concern of serious investigation throughout the evolution of scientific thought. As early as the fifth century B. C. questions regarding motion were presented as touchstones for the most fundamental concepts about existence. Such wide ranging philosophical issues are beyond the scope of this book, however, consider the paradox of the flying arrow attri buted to Zeno of Elea: An arrow is shot from point A to point B requiring a sequence of time instants to traverse the distance. Now, for any time instant, T, of the sequence the arrow is at a position, Pi' and at Ti+! the i arrow is at Pi+i> with Pi ::I-P+* Clearly, each Ti must be a singular time i 1 unit at which the arrow is at rest at Pi because if the arrow were moving during Ti there would be a further sequence, Til' of time instants required for the arrow to traverse the smaller distance. Now, regardless of the level to which this recursive argument is applied, one is left with the flight of the arrow comprising a sequence of positions at which the arrow is at rest. The original intent of presenting this paradox has been interpreted to be as an argument against the possibility of individuated objects moving in space.

This book reflects the current industrial interest and investment in process control systems. The use of computer systems in process control can provide great benefits, and it is estimated that efficiency can be increased by up to 30%. It is not surprising, therefore, that there have been considerable efforts by system designers and users to introduce and use such systems. Process hardware is integrated into a complete production system through data processing. It is for this purpose that technical specialists (eg electrical, mechanical, electronics, communication and process engineers and programmers) are involved in data processing. The scope of this book is therefore to assist in the selction of computer hardware and software that match the functional specification of the data processing component of a particular system.

This book has been motivated by an urgent need for designing and implementation of innovative control algorithms and systems for tracked vehicles. Nowadays the unmanned vehicles are becoming more and more common. Therefore there is a need for innovative mechanical constructions capable of adapting to various applications regardless the ground, air or water/underwater environment. There are multiple various activities connected with tracked vehicles. They can be distributed among three main groups: design and control algorithms, sensoric and vision based in-formation, construction and testing mechanical parts of unmanned vehicles. Scientists and researchers involved in mechanics, control algorithms, image processing, computer vision, data fusion, or IC will find this book useful.

The purpose of this monograph is to give the broad aspects of nonlinear identification and control using neural networks. It consists of three parts:- an introduction to the fundamental principles of neural networks;- several methods for nonlinear identification using neural networks;- various techniques for nonlinear control using neural networks.A number of simulated and industrial examples are used throughout the monograph to demonstrate the operation of nonlinear identification and control techniques using neural networks. It should be emphasised that the methods and systems of nonlinear control have not progressed as rapidly as those for linear control. Comparatively speaking, at the present time, they are still in the development stage. We believe that the fundamental theory, various design methods and techniques, and several applications of nonlinear identification and control using neural networks that are presented in this monograph will enable the reader to analyse and synthesise nonlinear control systems quantitatively.

With businesses becoming ever more competitive, marketing strategies need to be more precise and performance oriented. Companies are investing considerably in analytical infrastructure for marketing. This new volume, Marketing Analytics: A Machine Learning Approach, enlightens readers on the application of analytics in marketing and the process of analytics, providing a foundation on the concepts and algorithms of machine learning and statistics. The book simplifies analytics for businesses and explains its uses in different aspects of marketing in a way that even marketers with no prior analytics experience will find it easy to follow, giving them to tools to make better business decisions. This volume gives a comprehensive overview of marketing analytics, incorporating machine learning methods of data analysis that automates analytical model building. The volume covers the important aspects of marketing analytics, including segmentation and targeting analysis, statistics for marketing, marketing metrics, consumer buying behavior, neuromarketing techniques for consumer analytics, new product development, forecasting sales and price, web and social media analytics, and much more. This well-organized and straight-forward volume will be valuable for marketers, managers, decision makers, and research scholars, and faculty in business marketing and information technology and would also be suitable for classroom use.

The book presents the modeling and control of hydrogen-air PEM fuel cells, including simultaneous estimation of the parameters and states, fuzzy cluster modeling, SPM-based predictive control and advanced fuzzy control. MATLAB/Simulink-based modeling and control programs are discussed in detail. With simulations and experiments, it is an essential reference for both scientists and industrial engineers.

Control Theory is at the heart of information and communication technologies of complex systems. It can contribute to meeting the energy and environmental challenges we are facing.

The textbook is organized in the way an engineer classically proceeds to solve a control problem, that is, elaboration of a mathematical model capturing the process behavior, analysis of this model and design of a control to achieve the desired objectives.

It is divided into three Parts. The first part of the text addresses modeling aspects through state space and input-output representations. The notion of the internal state of a system (for example mechanical, thermal or electrical), as well as its description using a finite number of variables, is also emphasized. The second part is devoted to the stability analysis of an equilibrium point. The authors present classical tools for stability analysis, such as linearization techniques and Lyapunov functions.

Central to Control Theory are the notions of feedback and of closed-loop, and the third part of the textbook describes the linear control synthesis in a continuous and discrete-time framework and also in a probabilistic context. Quadratic optimization and Kalman filtering are presented, as well as the polynomial representation, a convenient approach to reject perturbations on the system without making the control law more complex. Throughout the text, different examples are developed, both in the chapters and in the exercises.

This monograph presents recent advances in differential flatness theory and analyzes its use for nonlinear control and estimation. It shows how differential flatness theory can provide solutions to complicated control problems, such as those appearing in highly nonlinear multivariable systems and distributed-parameter systems. Furthermore, it shows that differential flatness theory makes it possible to perform filtering and state estimation for a wide class of nonlinear dynamical systems and provides several descriptive test cases. The book focuses on the design of nonlinear adaptive controllers and nonlinear filters, using exact linearization based on differential flatness theory. The adaptive controllers obtained can be applied to a wide class of nonlinear systems with unknown dynamics, and assure reliable functioning of the control loop under uncertainty and varying operating conditions. The filters obtained outperform other nonlinear filters in terms of accuracy of estimation and computation speed. The book presents a series of application examples to confirm the efficiency of the proposed nonlinear filtering and adaptive control schemes for various electromechanical systems. These include: * industrial robots; * mobile robots and autonomous vehicles; * electric power generation; * electric motors and actuators; * power electronics;* internal combustion engines; * distributed-parameter systems; and * communication systems. Differential Flatness Approaches to Nonlinear Control and Filtering will be a useful reference for academic researchers studying advanced problems in nonlinear control and nonlinear dynamics, and for engineers working on control applications in electromechanical systems.

"Dynamic Response of Linear Mechanical Systems: Modeling, Analysis and Simulation" can be utilized for a variety of courses, including junior and senior-level vibration and linear mechanical analysis courses. The author connects, by means of a rigorous, yet intuitive approach, the theory of vibration with the more general theory of systems. The book features:

A seven-step modeling technique that helps structure the rather unstructured process of mechanical-system modeling

A system-theoretic approach to deriving the time response of the linear mathematical models of mechanical systems

The modal analysis and the time response of two-degree-of-freedom systems-the first step on the long way to the more elaborate study of multi-degree-of-freedom systems-using the Mohr circle

Simple, yet powerful simulation algorithms that exploit the linearity of the system for both single- and multi-degree-of-freedom systems

Examples and exercises that rely on modern computational toolboxes for both numerical and symbolic computations as well as a Solutions Manual for instructors, with complete solutions of a sample of end-of-chapter exercises

Chapters 3 and 7, on simulation, include in each "Exercises" section a set of miniprojects that require code-writing to implement the algorithms developed in these chapters

Computer vision-based crack-like object detection has many useful applications, such as pavement surface inspection, underground pipeline inspection, bridge cracking monitoring, railway track assessment, etc. However, in most contexts, cracks appear as thin, irregular long-narrow objects, and often are buried into complex, textured background with high diversity which make the crack detection very challenging. During the past a few years, the deep learning technique has achieved great success and has been utilized for solving a variety of object detection problems. However, using deep learning for accurate crack localization is non-trivial. This book discusses crack-like object detection problem in a comprehensive way. It starts by discussing traditional image processing approaches for solving this problem, and then introduces deep learning-based methods. The book provides a comprehensive review of object detection problems and focuses on the most challenging problem, crack-like object detection, to dig deep into the deep learning method. It includes examples of real-world problems, which are easy to understand and could be a good tutorial for introducing computer vision and machine learning.

This volume contains revised and extended research articles written by prominent researchers participating in the ICF4C 2011 conference. 2011 International Conference on Future Communication, Computing, Control and Management (ICF4C 2011) has been held on December 16-17, 2011, Phuket, Thailand. Topics covered include intelligent computing, network management, wireless networks, telecommunication, power engineering, control engineering, Signal and Image Processing, Machine Learning, Control Systems and Applications, The book will offer the states of arts of tremendous advances in Computing, Communication, Control, and Management and also serve as an excellent reference work for researchers and graduate students working on Computing, Communication, Control, and Management Research.

In the past decade a critical mass of work that uses fuzzy logic for autonomous vehicle navigation has been reported. Unfortunately, reports of this work are scattered among conference, workshop, and journal publications that belong to different research communities (fuzzy logic, robotics, artificial intelligence, intelligent control) and it is therefore not easily accessible either to the new comer or to the specialist. As a result, researchers in this area may end up reinventing things while being unaware of important existing work. We believe that research and applications based on fuzzy logic in the field of autonomous vehicle navigation have now reached a sufficient level of maturity, and that it should be suitably reported to the largest possible group of interested practitioners, researches, and students. On these grounds, we have endeavored to collect some of the most representative pieces of work in one volume to be used as a reference. Our aim was to provide a volume which is more than "yet another random collection of papers," and gives the reader some added value with respect to the individual papers. In order to achieve this goal we have aimed at: * Selecting contributions which are representative of a wide range of prob lems and solutions and which have been validated on real robots; and * Setting the individual contributions in a clear framework, that identifies the main problems of autonomous robotics for which solutions based on fuzzy logic have been proposed.

Robot intelligence has become a major focus of intelligent robotics. Recent innovation in computational intelligence including fuzzy learning, neural networks, evolutionary computation and classical Artificial Intelligence provides sufficient theoretical and experimental foundations for enabling robots to undertake a variety of tasks with reasonable performance. This book reflects the recent advances in the field from an advanced knowledge processing perspective; there have been attempts to solve knowledge based information explosion constraints by integrating computational intelligence in the robotics context.

Hopping, climbing and swimming robots, nano-size neural networks, motorless walkers, slime mould and chemical brains - "Artificial Life Models in Hardware" offers unique designs and prototypes of life-like creatures in conventional hardware and hybrid bio-silicon systems. Ideas and implementations of living phenomena in non-living substrates cast a colourful picture of state-of-art advances in hardware models of artificial life.

This collection of proceedings from the International Conference on Systems Engineering, Las Vegas, 2014 is orientated toward systems engineering, including topics like aero-space, power systems, industrial automation and robotics, systems theory, control theory, artificial intelligence, signal processing, decision support, pattern recognition and machine learning, information and communication technologies, image processing, and computer vision as well as its applications. The volume's main focus is on models, algorithms, and software tools that facilitate efficient and convenient utilization of modern achievements in systems engineering.

Most ocean vessels are underactuated but control of their motion in the real ocean environment is essential. Starting with a review of the background on ocean-vessel dynamics and nonlinear control theory, the authors' systematic approach is based on various nontrivial coordinate transformations coupled with advanced nonlinear control design methods. This strategy is then used for the development and analysis of a number of ocean-vessel control systems with the aim of achieving advanced motion control tasks including stabilization, trajectory-tracking, path-tracking and path-following.

Control of Ships and Underwater Vehicles offers the reader: - new results in the nonlinear control of underactuated ocean vessels; - efficient designs for the implementation of controllers on underactuated ocean vessels; - numerical simulations and real-time implementations of the control systems designed on a scale-model ship for each controller developed to illustrate their effectiveness and afford practical guidance.

The International Conference on the Theory of Machines and Mechanisms is organized every four years, under the auspices of the International Federation for the Promotion of Mechanism and Machine Science (IFToMM) and the Czech Society for Mechanics. This eleventh edition of the conference took place at the Technical University of Liberec, Czech Republic, 4-6 September 2012. This volume offers an international selection of the most important new results and developments, in 73 papers, grouped in seven different parts, representing a well-balanced overview, and spanning the general theory of machines and mechanisms, through analysis and synthesis of planar and spatial mechanisms, dynamics of machines and mechanisms, linkages and cams, computational mechanics, rotor dynamics, biomechanics, mechatronics, vibration and noise in machines, optimization of mechanisms and machines, control and monitoring systems of machines, accuracy and reliability of machines and mechanisms, robots and manipulators to the mechanisms of textile machines.

Intended for self-study, this second volume presents a systematic approach for deriving model equations of planar and spatial mechanisms. The necessary theoretical foundations have been laid in the first volume. The focus is on the application of the modeling methodology to various examples of rigid-body mechanisms, simple planar ones as well as more challenging spatial problems. A rich variety of joint models, active constraints, as well as active and passive force elements is treated. The book is intended for self-study by working engineers and students concerned with the control of mechanical systems, i.e. robotics, mechatronics, vehicles, and machine tools. Its examples can be used as models for university lectures.

Evolutionary algorithms (EAs) are becoming increasingly attractive for researchers from various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science, economics, etc. This book presents an insightful, comprehensive, and up-to-date treatment of EAs, such as genetic algorithms, differential evolution, evolution strategy, constraint optimization, multimodal optimization, multiobjective optimization, combinatorial optimization, evolvable hardware, estimation of distribution algorithms, ant colony optimization, particle swarm optimization, artificial immune systems, artificial life, genetic programming, etc.

It emphasises the initiative ideas of the algorithm, contains discussions in the contexts, and suggests further readings and possible research projects. All the methods form a pedagogical way to make EAs easy and interesting.

This textbook also introduces the applications of EAs as many as possible. At least one real-life application is introduced by the end of almost every chapter. The authors focus on the kernel part of applications, such as how to model real-life problems, how to encode and decode the individuals, how to design effective search operators according to the chromosome structures, etc.

This textbook adopts pedagogical ways of making EAs easy and interesting. Its methods include an introduction at the beginning of each chapter, emphasising the initiative, discussions in the contexts, summaries at the end of every chapter, suggested further reading, exercises, and possible research projects.

Introduction to Evolutionary Algorithms will enable students to:

establish a strong background on evolutionary algorithms;

appreciate the cutting edge of EAs;

perform their own research projects by simulating the application introduced in the book; and

apply their intuitive ideas to academic search.

This book is aimed at senior undergraduate students or first-year graduate students as a textbook or self-study material."

This volume contains the proceedings of the IUTAM Symposium on Model Order Reduction of Coupled System, held in Stuttgart, Germany, May 22-25, 2018. For the understanding and development of complex technical systems, such as the human body or mechatronic systems, an integrated, multiphysics and multidisciplinary view is essential. Many problems can be solved within one physical domain. For the simulation and optimization of the combined system, the different domains are connected with each other. Very often, the combination is only possible by using reduced order models such that the large-scale dynamical system is approximated with a system of much smaller dimension where the most dominant features of the large-scale system are retained as much as possible. The field of model order reduction (MOR) is interdisciplinary. Researchers from Engineering, Mathematics and Computer Science identify, explore and compare the potentials, challenges and limitations of recent and new advances.

This book presents new approaches to constructing fuzzy models for model-based control. Simulated examples and real-world applications from chemical and process engineering illustrate the main methods and techniques. Supporting MATLAB and Simulink files create a computational platform for exploration of the concepts and algorithms.

Since the late 1960s, there has been a revolution in robots and industrial automation, from the design of robots with no computing or sensorycapabilities (first-generation), to the design of robots with limited computational power and feedback capabilities (second-generation), and the design of intelligent robots (third-generation), which possess diverse sensing and decision making capabilities. The development of the theory of intelligent machines has been developed in parallel to the advances in robot design. This theory is the natural outcome of research and development in classical control (1950s), adaptive and learning control (1960s), self-organizing control (1970s) and intelligent control systems (1980s). The theory of intelligent machines involves utilization and integration of concepts and ideas from the diverse disciplines of science, engineering and mathematics, and fields like artificial intelligence, system theory and operations research. The main focus and motivation is to bridge the gap between diverse disciplines involved and bring under a common cover several generic methodologies pertaining to what has been defined as machine intelligence. Intelligent robotic systems are a specific application of intelligent machines. They are complex computer controlled robotic systems equipped with a diverse set of visual and non visual sensors and possess decision making and problem solving capabilities within their domain of operation. Their modeling and control is accomplished via analytical and heuristic methodologies and techniques pertaining to generalized system theory and artificial intelligence. Intelligent Robotic Systems: Theory, Design and Applications, presents and justifies the fundamental concepts and ideas associated with the modeling and analysis of intelligent robotic systems. Appropriate for researchers and engineers in the general area of robotics and automation, Intelligent Robotic Systems is both a solid reference as well as a text for a graduate level course in intelligent robotics/machines.

In recent yearswe haveseen considerableadvances in the development of - manoid robots, that is robots with an anthropomorphic design. Such robots should be capable of autonomously performing tasks for their human users in changing environments by adapting to these and to the circumstances at hand. To do so, they as well as any kind of autonomous robot need to have some way of understanding the world around them. We humans do so by our senses, both our far senses vision and hearing (smelling too) and our near senses touch and taste. Vision plays a special role in the way it simulta- ously tells us "where" and "what" in a direct way. It is therefore an accepted factthatto developautonomousrobots,humanoidornot,itisessentialto- clude competent systems for visual perception. Such systems should embody techniques from the ?eld of computer vision, in which sophisticated com- tational methods for extracting information from visual imagery have been developed over a number of decades. However, complete systems incorpor- ing such advanced techniques, while meeting the requirements of real-time processing and adaptivity to the complexity that even our everyday envir- ment displays, are scarce. The present volume takes an important step for ?lling this gap by presenting methods and a system for visual perception for a humanoid robot with speci?c applications to manipulation tasks and to how the robot can learn by imitating the human.

Hybrid dynamical systems, both continuous and discrete dynamics and variables, have attracted considerable interest recently. This emerging area is found at the interface of control theory and computer engineering, focusing on the analogue and digital aspects of systems and devices. They are essential for advances in modern digital- controller technology. "Qualitative Theory of Hybrid Dynamical Systems" provides a thorough development and systematic presentation of the foundations and framework for hybrid dynamical systems. The presentation offers an accessible, but precise, development of the mathematical models, conditions for existence of limit cycles, and criteria of their stability. The book largely concentrates on the case of discretely controlled continuous-time systems and their relevance for modeling aspects of flexible manufacturing systems and dynamically routed queuing networks. Features and topics: *differential automata*development and use of the concept "cyclic linear differential automata" (CLDA)*switched single-server flow networks coverage*application to specific models of manufacturing systems and queuing networks*select collection of open problems for the subject*self-contained presentation of topics, with the necessary background This new book is an excellent resource for the study and analysis of hybrid dynamical systems used in systems and control engineering. Researchers, postgraduates and professionals in control engineering and computer engineering will find the book an up-to-date development of the relevant new concepts and tools.

"There are three words that characterize this work: thoroughness, completeness and clarity. The authors are congratulated for taking the time to write an excellent linear systems textbook! a ]The authors have used their mastery of the subject to produce a textbook that very effectively presents the theory of linear systems as it has evolved over the last thirty years. The result is a comprehensive, complete and clear exposition that serves as an excellent foundation for more advanced topics in system theory and control." a "IEEE Transactions on Automatic Control

"In assessing the present book as a potential textbook for our first graduate linear systems course, I find...[that] Antsaklis and Michel have contributed an expertly written and high quality textbook to the field and are to be congratulateda ]. Because of its mathematical sophistication and completeness the present book is highly recommended for use, both as a textbook as well as a reference." a "Automatica

Linear systems theory plays a broad and fundamental role in electrical, mechanical, chemical and aerospace engineering, communications, and signal processing. A thorough introduction to systems theory with emphasis on control is presented in this self-contained textbook.

The book examines the fundamental properties that govern the behavior of systems by developing their mathematical descriptions. Linear time-invariant, time-varying, continuous-time, and discrete-time systems are covered. Rigorous development of classic and contemporary topics in linear systems, as well as extensive coverage of stability and polynomial matrix/fractional representation, provide the necessary foundation for further study of systemsand control.

Linear Systems is written as a textbook for a challenging one-semester graduate course; a solutions manual is available to instructors upon adoption of the text. The booka (TM)s flexible coverage and self-contained presentation also make it an excellent reference guide or self-study manual.

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For a treatment of linear systems that focuses primarily on the time-invariant case using streamlined presentation of the material with less formal and more intuitive proofs, see the authorsa (TM) companion book entitled A Linear Systems Primer.