This book meets head-on the difficulty of making practical use of new systems theory, presenting a selection of varied applications together with relevant theory. It shows how workable identification and control solutions can be derived by adapting and extrapolating from the theory. Each chapter has a common structure: a brief presentation of theory; the description of a particular application; experimental results; and a section highlighting, explaining and laying out solutions to the discrepancy between the theoretical and the practical.

Networked and Distributed Predictive Control presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems - the first book to do so. The design of model predictive control systems using Lyapunov-based techniques accounting for the influence of asynchronous and delayed measurements is followed by a treatment of networked control architecture development. This shows how networked control can augment dedicated control systems in a natural way and takes advantage of additional, potentially asynchronous and delayed measurements to maintain closed loop stability and significantly to improve closed-loop performance. The text then shifts focus to the design of distributed predictive control systems that cooperate efficiently in computing optimal manipulated input trajectories that achieve desired stability, performance and robustness specifications but spend a fraction of the time required by centralized control systems. Key features of this book include: * new techniques for networked and distributed control system design; * insight into issues associated with networked and distributed predictive control and their solution; * detailed appraisal of industrial relevance using computer simulation of nonlinear chemical process networks and wind- and solar-energy-generation systems; and * integrated exposition of novel research topics and rich resource of references to significant recent work. A full understanding of Networked and Distributed Predictive Control requires a basic knowledge of differential equations, linear and nonlinear control theory and optimization methods and the book is intended for academic researchers and graduate students studying control and for process control engineers. The constant attention to practical matters associated with implementation of the theory discussed will help each of these groups understand the application of the book's methods in greater depth.

This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their applications in areas such as: intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and optimization of complex problems. The book is divided into five main parts. The first part proposes new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications; the second explores new concepts and algorithms in neural networks and fuzzy logic applied to recognition. The third part examines the theory and practice of meta-heuristics in various areas of application, while the fourth highlights diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical contexts. Finally, the fifth part focuses on applications of fuzzy logic, neural networks and meta-heuristics to robotics problems.

This book gathers the latest advances, innovations and applications in the field of robotics and mechatronics, as presented by leading international researchers and engineers at the 6th IFToMM International Symposium on Robotics and Mechatronics (ISRM), held in Taipei, Taiwan, on October 28-30, 2019. It covers highly diverse topics, including mechanism synthesis, analysis, and design, kinematics and dynamics of multibody systems, modelling and simulation, sensors and actuators, novel robotic systems, industrial- and service-related robotics and mechatronics, medical robotics, and historical developments in robotics and mechatronics. The contributions, which were selected through a rigorous international peer-review process, share exciting ideas that spur novel research directions and foster new, multidisciplinary collaborations.

MR technologies play an increasing role in different aspects of human-robot interactions. The visual combination of digital contents with real working spaces creates a simulated environment that is set out to enhance these aspects. This book presents and discusses fundamental scientific issues, technical implementations, lab testing, and industrial applications and case studies of Mixed Reality in Human-Robot Interaction. It is a reference book that not only acts as meta-book in the field that defines and frames Mixed Reality use in Human-Robot Interaction, but also addresses up-coming trends and emerging directions of the field.

This volume offers a comprehensive reference volume to the state-of-the-art in the area of MR in Human-Robot Interaction, an excellent mix of contributions from leading researcher/experts in multiple disciplines from academia and industry. All authors are experts and/or top researchers in their respective areas and each of the chapters has been rigorously reviewed for intellectual contents by the editorial team to ensure a high quality. This book provides up-to-date insight into the current research topics in this field as well as the latest technological advancements and the best working examples.

This book presents, in a comprehensive way, current unmanned aviation regulation, airworthiness certification, special aircraft categories, pilot certification, federal aviation requirements, operation rules, airspace classes and regulation development models. It discusses unmanned aircraft systems levels of safety derived mathematically based on the corresponding levels for manned aviation. It provides an overview of the history and current status of UAS airworthiness and operational regulation worldwide. Existing regulations have been developed considering the need for a complete regulatory framework for UAS. It focuses on UAS safety assessment and functional requirements, achieved in terms of defining an "Equivalent Level of Safety," or ELOS, with that of manned aviation, specifying what the ELOS requirement entails for UAS regulations. To accomplish this, the safety performance of manned aviation is first evaluated, followed by a novel model to derive reliability requirements for achieving target levels of safety (TLS) for ground impact and mid-air collision accidents.It discusses elements of a viable roadmap leading to UAS integration in to the NAS. For this second edition of the book almost all chapters include major updates and corrections. There is also a new appendix chapter.

This monograph describes a new family of algorithms for the simultaneous localization and mapping (SLAM) problem in robotics, called FastSLAM. The FastSLAM-type algorithms have enabled robots to acquire maps of unprecedented size and accuracy, in a number of robot application domains and have been successfully applied in different dynamic environments, including a solution to the problem of people tracking.

This book presents up-to-date research and novel methodologies on fault diagnosis and fault tolerant control for switched linear systems. It provides a unified yet neat framework of filtering, fault detection, fault diagnosis and fault tolerant control of switched systems. It can therefore serve as a useful textbook for senior and/or graduate students who are interested in knowing the state-of-the-art of filtering, fault detection, fault diagnosis and fault tolerant control areas, as well as recent advances in switched linear systems.

Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we stand and where we should go from here.

Discrete Control Systems establishes a basis for the analysis and design of discretized/quantized control systems for continuous physical systems. Beginning with the necessary mathematical foundations and system-model descriptions, the text moves on to derive a robust stability condition. To keep a practical perspective on the uncertain physical systems considered, most of the methods treated are carried out in the frequency domain. As part of the design procedure, modified Nyquist-Hall and Nichols diagrams are presented and discretized proportional-integral-derivative control schemes are reconsidered. Schemes for model-reference feedback and discrete-type observers are proposed. Although single-loop feedback systems form the core of the text, some consideration is given to multiple loops and nonlinearities. The robust control performance and stability of interval systems (with multiple uncertainties) are outlined. Finally, the monograph describes the relationship between feedback-control and discrete event systems. The nonlinear phenomena associated with practically important event-driven systems are elucidated. The dynamics and stability of finite-state and discrete-event systems are defined. Academic researchers interested in the uses of discrete modelling and control of continuous systems will find Discrete Control Systems instructive. The inclusion of end-of-chapter problems also makes the book suitable for use in self study either by professional control engineers or graduate students supplementing a more formal regimen of learning.

An instructive reference that will help control researchers and engineers, interested in a variety of industrial processes, to take advantage of a powerful tuning method for the ever-popular PID control paradigm. This monograph presents explicit PID tuning rules for linear control loops regardless of process complexity. It shows the reader how such loops achieve zero steady-position, velocity, and acceleration errors and are thus able to track fast reference signals. The theoretical development takes place in the frequency domain by introducing a general-transfer-function-known process model and by exploiting the principle of the magnitude optimum criterion. It is paralleled by the presentation of real industrial control loops used in electric motor drives. The application of the proposed tuning rules to a large class of processes shows that irrespective of the complexity of the controlled process the shape of the step and frequency response of the control loop exhibits a specific performance. This specific performance, along with the PID explicit solution, formulates the basis for developing an automatic tuning method for the PID controller parameters which is a problem often met in many industry applications-temperature, pH, and humidity control, ratio control in product blending, and boiler-drum level control, for example. The process of the model is considered unknown and controller parameters are tuned automatically such that the aforementioned performance is achieved. The potential both for the explicit tuning rules and the automatic tuning method is demonstrated using several examples for benchmark process models recurring frequently in many industry applications.

Over the past decades, fault diagnosis (FDI) and fault tolerant control strategies (FTC) have been proposed based on different techniques for linear and nonlinear systems. Indeed a considerable attention is deployed in order to cope with diverse damages resulting in faults occurrence.

This book provides the most important steps and concerns in the design of estimation and control algorithms for induction motors. A single notation and modern nonlinear control terminology is used to make the book accessible, although a more theoretical control viewpoint is also given. Focusing on the induction motor with, the concepts of stability and nonlinear control theory given in appendices, this book covers: speed sensorless control; design of adaptive observers and parameter estimators; a discussion of nonlinear adaptive controls containing parameter estimation algorithms; and comparative simulations of different control algorithms. The book sets out basic assumptions, structural properties, modelling, state feedback control and estimation algorithms, then moves to more complex output feedback control algorithms, based on stator current measurements, and modelling for speed sensorless control. The induction motor exhibits many typical and unavoidable nonlinear features.

"Team Cooperation in a Network of Multi-Vehicle Unmanned Systems" develops a framework for modeling and control of a network of multi-agent unmanned systems in a cooperative manner and with consideration of non-ideal and practical considerations. The main focus of this book is the development of synthesis-based algorithms rather than on conventional analysis-based approaches to the team cooperation, specifically the team consensus problems. The authors provide a set of modified design-based consensus algorithms whose optimality is verified through introduction of performance indices. "

This volume is a collection of research studies on the modeling of emotions in complex autonomous systems. Several experts in the field are reporting their efforts and reviewing the literature in order to shed lights on how the processes of coding and decoding emotional states took place in humans, which are the physiological, physical, and psychological variables involved, invent new mathematical models and algorithms to describe them, and motivate these investigations in the light of observable societal changes and needs, such as the aging population and the cost of health care services. The consequences are the implementation of emotionally and socially believable machines, acting as helpers into domestic spheres, where emotions drive behaviors and actions. The contents of the book are highly multidisciplinary since the modeling of emotions in robotic socially believable systems requires a holistic perspective on topics coming from different research domains such as computer science, engineering, sociology, psychology, linguistic, and information communication. The book is of interest both to experts and students since last research works on a so complex multidisciplinary topic are described in a neat and didactical scientific language.

The integrated and advanced science research topic Man-Machine-Environment system engineering (MMESE) was first established in China by Professor Shengzhao Long in 1981, with direct support from one of the greatest modern Chinese scientists, Xuesen Qian. In a letter to Shengzhao Long from October 22nd, 1993, Xuesen Qian wrote: You have created a very important modern science and technology in China
MMESE primarily focuses on the relationship between man, machines and the environment, studying the optimum combination of man-machine-environment systems. In this system, man refers to people in the workplace (e.g. operators, decision-makers); machine is the general name for any object controlled by man (including tools, machinery, computers, systems and technologies), and environment describes the specific working conditions under which man and machine interact (e.g. temperature, noise, vibration, hazardous gases etc.). The three goals of optimization of Man-Machine-Environment systems are to ensure safety, efficiency and economy.
"Proceedings of the 13th International Conference on Man-Machine-Environment System Engineering" are an academic showcase of the best papers selected from more than 400 submissions, introducing readers to the top research topics and the latest developmental trends in the theory and application of MMESE.
These proceedings are interdisciplinary studies on the concepts and methods of physiology, psychology, system engineering, computer science, environment science, management, education, and other related disciplines. Researchers and professionals working in these interdisciplinary fields and researchers on MMESE related topics will benefit from these proceedings."

This book contains selected papers that address a variety of topics related to the design, development and operation of unmanned and fully autonomous sailing boats. These papers were presented in the 9th International Robotic Sailing Conference, in association with the 9th World Robotic Sailing Championship that took place in Viana do Castelo, Portugal from the 5th to 10th of September 2016. The book is divided in three parts, each focusing on key aspects of robotic sailing. The first part addresses the design, construction and validation of autonomous sailboat platforms, including their rigs, appendages and control mechanisms. The second part is devoted to the development of sensors and algorithms to enhance the performance of robotic sailing boats, in terms of their speed, course control and manoeuvring ability. Finally, the papers in the last part are dedicated to the improvement of behaviours required for the accomplishment of complex autonomous missions. Robotic sailing is a relatively new multidisciplinary area of research, with a recognized great potential for persistent ocean observation. Using the wind for boat propulsion is something mankind has been doing for centuries. Automating and optimizing the sailing process in the harsh marine environment is an ever present challenge which is now promising to bear fruit.

This book presents a domain of extreme industrial and scientific interest: the study of smart systems and structures. It presents polytope projects as comprehensive physical and cognitive architectures that support the investigation, fabrication and implementation of smart systems and structures. These systems feature multifunctional components that can perform sensing, control, and actuation. In light of the fact that devices, tools, methodologies and organizations based on electronics and information technology for automation, specific to the third industrial revolution, are increasingly reaching their limits, it is essential that smart systems be implemented in industry. Polytope projects facilitate the utilization of smart systems and structures as key elements of the fourth industrial revolution. The book begins by presenting polytope projects as a reference architecture for cyber-physical systems and smart systems, before addressing industrial process synthesis in Chapter 2. Flow-sheet trees, cyclic separations and smart configurations for multi-component separations are discussed here. In turn, Chapter 3 highlights periodic features for drug delivery systems and networks of chemical reactions, while Chapter 4 applies conditioned random walks to polymers and smart materials structures. Chapter 5 examines self-assembly and self-reconfiguration at different scales from molecular to micro systems. Smart devices and technologies are the focus of chapter 6. Modular micro reactor systems and timed automata are examined in selected case studies. Chapter 7 focuses on inferential engineering designs, concept-knowledge, relational concept analysis and model driven architecture, while Chapter 8 puts the spotlight on smart manufacturing, industry 4.0, reference architectures and models for new product development and testing. Lastly, Chapter 9 highlights the polytope projects methodology and the prospects for smart systems and structures. Focusing on process engineering and mathematical modeling for the fourth industrial revolution, the book offers a unique resource for engineers, scientists and entrepreneurs working in chemical, biochemical, pharmaceutical, materials science or systems chemistry, students in various domains of production and engineering, and applied mathematicians.

Human-in-the-loop Learning and Control for Robot Teleoperation presents recent, research progress on teleoperation and robots, including human-robot interaction, learning and control for teleoperation with many extensions on intelligent learning techniques. The book integrates cutting-edge research on learning and control algorithms of robot teleoperation, neural motor learning control, wave variable enhancement, EMG-based teleoperation control, and other key aspects related to robot technology, presenting implementation tactics, adequate application examples and illustrative interpretations. Robots have been used in various industrial processes to reduce labor costs and improve work efficiency. However, most robots are only designed to work on repetitive and fixed tasks, leaving a gap with the human desired manufacturing effect.

Most biometric books are either extraordinarily technical for technophiles or extremely elementary for the lay person. Striking a balance between the two, Biometric Technology: Authentication, Biocryptography, and Cloud-Based Architecture is ideal for business, IT, or security managers that are faced with the task of making purchasing, migration, or adoption decisions. It brings biometrics down to an understandable level, so that you can immediately begin to implement the concepts discussed. Exploring the technological and social implications of widespread biometric use, the book considers the science and technology behind biometrics as well as how it can be made more affordable for small and medium-sized business. It also presents the results of recent research on how the principles of cryptography can make biometrics more secure. Covering biometric technologies in the cloud, including security and privacy concerns, the book includes a chapter that serves as a "how-to manual" on procuring and deploying any type of biometric system. It also includes specific examples and case studies of actual biometric deployments of localized and national implementations in the U.S. and other countries. The book provides readers with a technical background on the various biometric technologies and how they work. Examining optimal application in various settings and their respective strengths and weaknesses, it considers ease of use, false positives and negatives, and privacy and security issues. It also covers emerging applications such as biocryptography. Although the text can be understood by just about anybody, it is an ideal resource for corporate-level executives who are considering implementing biometric technologies in their organizations.

This book presents hardware-efficient algorithms and FPGA implementations for two robotic tasks, namely exploration and landmark determination. The work identifies scenarios for mobile robotics where parallel processing and selective shutdown offered by FPGAs are invaluable. The book proceeds to systematically develop memory-driven VLSI architectures for both the tasks. The architectures are ported to a low-cost FPGA with a fairly small number of system gates.

Modeling and Control of Batch Processes presents state-of-the-art techniques ranging from mechanistic to data-driven models. These methods are specifically tailored to handle issues pertinent to batch processes, such as nonlinear dynamics and lack of online quality measurements. In particular, the book proposes: a novel batch control design with well characterized feasibility properties; a modeling approach that unites multi-model and partial least squares techniques; a generalization of the subspace identification approach for batch processes; and applications to several detailed case studies, ranging from a complex simulation test bed to industrial data. The book's proposed methodology employs statistical tools, such as partial least squares and subspace identification, and couples them with notions from state-space-based models to provide solutions to the quality control problem for batch processes. Practical implementation issues are discussed to help readers understand the application of the methods in greater depth. The book includes numerous comments and remarks providing insight and fundamental understanding into the modeling and control of batch processes. Modeling and Control of Batch Processes includes many detailed examples of industrial relevance that can be tailored by process control engineers or researchers to a specific application. The book is also of interest to graduate students studying control systems, as it contains new research topics and references to significant recent work. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

Multisensor fusion systems are only practical if the algorithms used are practical and effective, and if there is efficient database support. The first part of this book discusses a wide range of issues related to the development of robust, context-sensitive, and efficient data fusion algorithms. The second part addresses database requirements, structures, and issues related to achieving overall computational efficiency. Featuring highly accessible notation, the processing model and database issues presented in the text are aimed at system developers working in sensor fusion, automatic target recognition, multiple-target tracking, robotic control, automated image understanding, and large-scale integration and fabrication.

This book reports on an outstanding research devoted to modeling and control of dynamic systems using fractional-order calculus. It describes the development of model-based control design methods for systems described by fractional dynamic models. More than 300 years had passed since Newton and Leibniz developed a set of mathematical tools we now know as calculus. Ever since then the idea of non-integer derivatives and integrals, universally referred to as fractional calculus, has been of interest to many researchers. However, due to various issues, the usage of fractional-order models in real-life applications was limited. Advances in modern computer science made it possible to apply efficient numerical methods to the computation of fractional derivatives and integrals. This book describes novel methods developed by the author for fractional modeling and control, together with their successful application in real-world process control scenarios.