The need to adapt to the demands of global supply chains in real-time is of significant importance to the future success of continuous process industries. Amongst such business drivers, it will become critical that process plants are designed to be easily reconfigured as and when necessary. Recent developments in process control have attempted to address this requirement, yet there has not been a systematic effort made on the analysis of the fundamental shortcomings in the modularity of process control systems.

A Distributed Coordination Approach to Reconfigurable Process Control presents research that addresses this critical question, via developing a new distributed framework that will enable the building of a process control system that is capable of reconfigurability. This framework views the process as a set of readily-integrated, modular process elements, which operate relatively independently and are each supported by a degree of stand-alone decision-making capability. The rationale and benefits of moving towards the new approach is demonstrated by means of a worked example of a real process plant.

A Distributed Coordination Approach to Reconfigurable Process Control will be a useful reference to both academic and industrial practitioners working in the field of design and integration of process control systems. The new architectural dimension presented in this research will also help end-users to gain an understanding of the economic aspects of material flows across their plants, and the ways in which their processes can be integrated across the enterprise.

This monograph discusses issues related to estimation, control, and motion planning for mobile robots operating in rough terrain, with particular attention to planetary exploration rovers. Rough terrain robotics is becoming increasingly important in space exploration, and industrial applications. However, most current motion planning and control algorithms are not well suited to rough terrain mobility, since they do not consider the physical characteristics of the rover and its environment. Specific addressed topics are: wheel terrain interaction modeling, including terrain parameter estimation and wheel terrain contact angle estimation; rough terrain motion planning; articulated suspension control; and traction control. Simulation and experimental results are presented that show that the desribed algorithms lead to improved mobility for robotic systems in rough terrain.

Systems with delays appear frequently in engineering; typical examples of time-delay systems are communication networks, chemical processes and tele-operation systems. The presence of delays makes system analysis and control design much more complicated. During the last decade, we have witnessed significant developments in robust control of time-delay systems. Robust Control of Time-delay Systems presents a systematic and comprehensive treatment for robust (H-infinity) control of such systems in the frequency domain. The emphasis is on systems with a single input or output delay, although the delay-free part of the plant can be multi-input-multi-output, in which case the delays in different channels should be the same.

This synthesis of the authora (TM)s recent work covers the whole range of robust control of time-delay systems: from controller parameterization and design to controller implementation; from the Nehari and one-block problems to the four-block problem; from theoretical developments to practical issues. The major tools used in this book are similarity transformation, the chain-scattering approach and J-spectral factorization. The idea is, in the words of Albert Einstein, to "make everything as simple as possible, but not simpler." A website associated with the book is a source of MATLABA(R) and SimulinkA(R) material which will assist with simulation and modelling of the material in the text.

Robust Control of Time-delay Systems is self-contained and will interest control theorists, researchers and mathematicians working with time-delay systems and engineers looking to design commercial controllers or to use them in plants or communication systems with time delays.Its methodical approach will also be of value to graduates studying either general robust control theory or its particular applications in time-delay systems.

Fault Detection and Fault-tolerant Control Using Sliding Modes is the first text dedicated to showing the latest developments in the use of sliding-mode concepts for fault detection and isolation (FDI) and fault-tolerant control in dynamical engineering systems. It begins with an introduction to the basic concepts of sliding modes to provide a background to the field. This is followed by chapters that describe the use and design of sliding-mode observers for FDI using robust fault reconstruction. The development of a class of sliding-mode observers is described from first principles through to the latest schemes that circumvent minimum-phase and relative-degree conditions. Recent developments have shown that the field of fault tolerant control is a natural application of the well-known robustness properties of sliding-mode control. A family of sliding-mode control designs incorporating control allocation, which can deal with actuator failures directly by exploiting redundancy, is presented. Various realistic case studies, specifically highlighting aircraft systems and including results from the implementation of these designs on a motion flight simulator, are described. A reference and guide for researchers in fault detection and fault-tolerant control, this book will also be of interest to graduate students working with nonlinear systems and with sliding modes in particular. Advances in Industrial Control aims to report and encourage 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.

This book focuses on the analysis and design of low-density parity-check (LDPC) coded modulations, which are becoming part of several current and future communication systems, such as high-throughput terrestrial and satellite wireless networks. In this book, a two-sided perspective on the design of LDPC coded systems is proposed, encompassing both code/modulation optimization (transmitter side) and detection algorithm design (receiver side). After introducing key concepts on error control coding, in particular LDPC coding, and detection techniques, the book presents several relevant applications. More precisely, by using advanced performance evaluation techniques, such as extrinsic information transfer charts, the optimization of coded modulation schemes are considered for (i) memoryless channels, (ii) dispersive and partial response channels, and (iii) concatenated systems including differential encoding. This book is designed to be used by graduate students working in the field of communication theory, with particular emphasis on LDPC coded communication schemes, and industry experts working on related fields.

The Proportional-Integral-Derivative (PID) controller operates the majority of modern control systems and has applications in many industries; thus any improvement in its design methodology has the potential to have a significant engineering and economic impact. Despite the existence of numerous methods for setting the parameters of PID controllers, the stability analysis of time-delay systems that use PID controllers remains extremely difficult and unclear, and there are very few existing results on PID controller synthesis.Filling a gap in the literature, this book is a presentation of recent results in the field of PID controllers, including their design, analysis, and synthesis. The focus is on linear time-invariant plants that may contain a time-delay in the feedback loop-a setting that captures many real-world practical and industrial situations. Emphasis is placed on the efficient computation of the entire set of PID controllers achieving stability and various performance specifications, which is important for the development of future software design packages, as well as further capabilities such as adaptive PID design and online implementation.

This book presents intuitive explanations of the principles of microgrids, including their structure and operation and their applications. It also discusses the latest research on microgrid control and protection technologies and the essentials of microgrids as well as enhanced communication systems. The book provides solutions to microgrid operation and planning issues using various methodologies including planning and modelling; AC and DC hybrid microgrids; energy storage systems in microgrids; and optimal microgrid operational planning. Written by specialists, it is filled in innovative solutions and research related to microgrid operation, making it a valuable resource for those interested in developing updated approaches in electric power analysis, design and operational strategies. Thanks to its in-depth explanations and clear, three-part structure, it is useful for electrical engineering students, researchers and technicians.

Identifying the input-output relationship of a system or discovering the evolutionary law of a signal on the basis of observation data, and applying the constructed mathematical model to predicting, controlling or extracting other useful information constitute a problem that has been drawing a lot of attention from engineering and gaining more and more importance in econo metrics, biology, environmental science and other related areas. Over the last 30-odd years, research on this problem has rapidly developed in various areas under different terms, such as time series analysis, signal processing and system identification. Since the randomness almost always exists in real systems and in observation data, and since the random process is sometimes used to model the uncertainty in systems, it is reasonable to consider the object as a stochastic system. In some applications identification can be carried out off line, but in other cases this is impossible, for example, when the structure or the parameter of the system depends on the sample, or when the system is time-varying. In these cases we have to identify the system on line and to adjust the control in accordance with the model which is supposed to be approaching the true system during the process of identification. This is why there has been an increasing interest in identification and adaptive control for stochastic systems from both theorists and practitioners."

"Control Performance Management in Industrial Automation "provides a coherent and self-contained treatment of a group of methods and applications of burgeoning importance to the detection and solution of problems with control loops that are vital in maintaining product quality, operational safety, and efficiency of material and energy consumption in the process industries. The monograph deals with all aspects of control performance management (CPM), from controller assessment (minimum-variance-control-based and advanced methods), to detection and diagnosis of control loop problems (process non-linearities, oscillations, actuator faults), to the improvement of control performance (maintenance, re-design of loop components, automatic controller re-tuning). It provides a contribution towards the development and application of completely self-contained and automatic methodologies in the field. Moreover, within this work, many CPM tools have been developed that goes far beyond available CPM packages.

"Control Performance Management in Industrial Automation"

. presents a comprehensive review of control performance assessment methods;

. develops methods and procedures for the detection and diagnosis of the root-causes of poor performance in complex control loops;

. covers important issues that arise when applying these assessment and diagnosis methods;

. recommends new approaches and techniques for the optimization of control loop performance based on the results of the control performance stage; and

. offers illustrative examples and industrial case studies drawn from chemicals, building, mining, pulp and paper, mineral and metal processing industries.

This book will be of interest to academic and industrial staff working on control systems design, maintenance or optimisation in all process industries."

The published material represents the outgrowth of teaching analytical optimization to aerospace engineering graduate students. To make the material available to the widest audience, the prerequisites are limited to calculus and differential equations. It is also a book about the mathematical aspects of optimal control theory. It was developed in an engineering environment from material learned by the author while applying it to the solution of engineering problems. One goal of the book is to help engineering graduate students learn the fundamentals which are needed to apply the methods to engineering problems. The examples are from geometry and elementary dynamical systems so that they can be understood by all engineering students. Another goal of this text is to unify optimization by using the differential of calculus to create the Taylor series expansions needed to derive the optimality conditions of optimal control theory.

This collection of twenty-three timely contributions covers a well-selected repertory of topics within the autonomous systems field. The book discusses a range of design, construction, control, and operation problems along with a multiplicity of well-established and novel solutions.

This book highlights the development of new methods for assessing and forecasting the state of various complex ageing systems in service; analyzing the influence of destabilizing factors on the accuracy of aircraft flight navigation support; and making recommendations on the ideal aircraft route, taking into consideration the available information on the reliability of the navigation and communication equipment.

This book provides an overview of the current research in the interdisciplinary area of personal assistants (PA) and cognitively inspired systems. It discusses the most relevant topics in this highly diversified domain, like reasoning, health, personalization, robotics, and ethical and social issues. Personal assistants (PA) are a relatively new concept directed at people with cognitive or physical disabilities, and is expanding to include complex platforms such as sensors, actuators, monitoring abilities and decision processes. Designed for a general audience, it is also of interest to undergraduates, graduates and researchers involved with intelligent systems, ambient intelligence or ambient assisted living. The content goes from an introduction of the field (aimed at undergraduates and a general readership) to specific and complex architectures (aimed at graduates and researchers).

This book showcases a subclass of hereditary systems, that is, systems with behaviour depending not only on their current state but also on their past history; it is an introduction to the mathematical theory of optimal control for stochastic difference Volterra equations of neutral type. As such, it will be of much interest to researchers interested in modelling processes in physics, mechanics, automatic regulation, economics and finance, biology, sociology and medicine for all of which such equations are very popular tools. The text deals with problems of optimal control such as meeting given performance criteria, and stabilization, extending them to neutral stochastic difference Volterra equations. In particular, it contrasts the difference analogues of solutions to optimal control and optimal estimation problems for stochastic integral Volterra equations with optimal solutions for corresponding problems in stochastic difference Volterra equations. Optimal Control of Stochastic Difference Volterra Equations commences with an historical introduction to the emergence of this type of equation with some additional mathematical preliminaries. It then deals with the necessary conditions for optimality in the control of the equations and constructs a feedback control scheme. The approximation of stochastic quasilinear Volterra equations with quadratic performance functionals is then considered. Optimal stabilization is discussed and the filtering problem formulated. Finally, two methods of solving the optimal control problem for partly observable linear stochastic processes, also with quadratic performance functionals, are developed. Integrating the author's own research within the context of the current state-of-the-art of research in difference equations, hereditary systems theory and optimal control, this book is addressed to specialists in mathematical optimal control theory and to graduate students in pure and applied mathematics and control engineering.

This is a cornerstone publication in robotic grasping. The authors have developed an internationally recognized expertise in this area. Additionally, they designed and built several prototypes which attracted the attention of the scientific community. The purpose of this book is to summarize years of research and to present, in an attractive format, the expertise developed by the authors on a new technology for grasping which has achieved great success both in theory and in practice.

This book gathers the Proceedings of the 6th International Conference on Robot Intelligence Technology and Applications (RITA 2018). Reflecting the conference's main theme, "Robotics and Machine Intelligence: Building Blocks for Industry 4.0," it features relevant and current research investigations into various aspects of these building blocks. The areas covered include: Instrumentation and Control, Automation, Autonomous Systems, Biomechatronics and Rehabilitation Engineering, Intelligent Systems, Machine Learning, Robotics, Sensors and Actuators, and Machine Vision, as well as Signal and Image Processing. A valuable asset, the book offers researchers and practitioners a timely overview of the latest advances in robot intelligence technology and its applications.

This book offers an overview of some recent advances in the Computational Bioacoustics methods and technology. In the focus of discussion is the pursuit of scalability, which would facilitate real-world applications of different scope and purpose, such as wildlife monitoring, biodiversity assessment, pest population control, and monitoring the spread of disease transmitting mosquitoes. The various tasks of Computational Bioacoustics are described and a wide range of audio parameterization and recognition tasks related to the automated recognition of species and sound events is discussed. Many of the Computational Bioacoustics methods were originally developed for the needs of speech, audio, or image processing, and afterwards were adapted to the requirements of automated acoustic recognition of species, or were elaborated further to address the challenges of real-world operation in 24/7 mode. The interested reader is encouraged to follow the numerous references and links to web resources for further information and insights. This book is addressed to Software Engineers, IT experts, Computer Science researchers, Bioacousticians, and other practitioners concerned with the creation of new tools and services, aimed at enhancing the technological support to Computational Bioacoustics applications. STTM, Speech Technology and Text Mining in Medicine and Health Care This series demonstrates how the latest advances in speech technology and text mining positively affect patient healthcare and, in a much broader sense, public health at large. New developments in text mining methods have allowed health care providers to monitor a large population of patients at any time and from any location. Employing advanced summarization techniques, patient data can be readily extracted from extensive clinical documents in electronic health records and immediately made available to the physician. These same summarization techniques can also aid the healthcare provider in extracting from the large corpora of medical literature the relevant information for treating the patient. The series topics include the design and acceptance of speech-enabled robots that assist in the operating room, studies of signal processing and acoustic modeling for speech and communication disorders, advanced statistical speech enhancement methods for creating synthetic voice, and technologies for addressing speech and language impairments. Titles in the Series consist of both authored books and edited contributions. All authored books and contributed works are peer-reviewed. The Series is for speech scientists and speech engineers, machine learning experts, biomedical engineers, medical speech pathologists, linguists, and healthcare professionals

This is the first book to provide a comprehensive and systematic introduction to the ranking methods for interval-valued intuitionistic fuzzy sets, multi-criteria decision-making methods with interval-valued intuitionistic fuzzy sets, and group decision-making methods with interval-valued intuitionistic fuzzy preference relations. Including numerous application examples and illustrations with tables and figures and presenting the authors' latest research developments, it is a valuable resource for researchers and professionals in the fields of fuzzy mathematics, operations research, information science, management science and decision analysis.

The quadratic cost optimal control problem for systems described by linear ordinary differential equations occupies a central role in the study of control systems both from a theoretical and design point of view. The study of this problem over an infinite time horizon shows the beautiful interplay between optimality and the qualitative properties of systems such as controllability, observability, stabilizability, and detectability. This theory is far more difficult for infinite dimensional systems such as those with time delays and distributed parameter systems. This reorganized, revised, and expanded edition of a two-volume set is a self-contained account of quadratic cost optimal control for a large class of infinite dimensional systems. The book is structured into five parts. Part I reviews basic optimal control and game theory of finite dimensional systems, which serves as an introduction to the book. Part II deals with time evolution of some generic controlled infinite dimensional systems and contains a fairly complete account of semigroup theory. theory in delay differential and partial differential equations. Part III studies the generic qualitative properties of controlled systems. Parts IV and V examine the optimal control of systems when performance is measured via a quadratic cost. Boundary control of parabolic and hyperbolic systems and exact controllability are also covered. Part I on finite dimensional controlled dynamical systems contains new material: an expanded chapter on the control of linear systems including a glimpse into H8 theory and dissipative systems, and a new chapter on linear quadratic two-person zero-sum differential games. A unique chapter, new to the second edition, brings together advanced concepts and techniques of semigroup theory and interpolation of linear operators that are usually treated independently. The material on delay systems and structural operators is not available elsewhere in book form.Control of infinite dimensional systems has a wide range and growing number of challenging applications. arise from new phenomenological studies, new technological developments, and more stringent design requirements. It will be useful for mathematicians, graduate students, and engineers interested in the field and in the underlying conceptual ideas of systems and control.

The area of adaptive systems, which encompasses recursive identification, adaptive control, filtering, and signal processing, has been one of the most active areas of the past decade. Since adaptive controllers are fundamentally nonlinear controllers which are applied to nominally linear, possibly stochastic and time-varying systems, their theoretical analysis is usually very difficult. Nevertheless, over the past decade much fundamental progress has been made on some key questions concerning their stability, convergence, performance, and robustness. Moreover, adaptive controllers have been successfully employed in numerous practical applications, and have even entered the marketplace.

This volume is intended for researchers in engineering and applied mathematics. It can also be used as a textbook for graduate students dealing with non-linear systems and control theory. After a self-contained treatment of the differential-geometric prerequisites, the book deals with controllability and observability properties of nonlinear systems, as well as various ways to obtain input-output representations. Problems of transforming nonlinear systems into simpler forms are discussed, including the feedback linearization problem. The disturbance and input-output decoupling problem are treated in detail, as well as some aspects of feedback stabilization, and interconnection and inversion of nonlinear systems. Emphasis is put on fundamental notions as (controlled) invariant distributions and submanifolds, together with algorithms to compute the required feedbacks. Extensions of these methods to other synthesis problems are indicated in the exercises at the end of each chapter. Special attention is paid to mechanical nonlinear control systems, and finally the theory is extended to general continuous-time and discrete time systems. Numerous examples and exercises illustrate the main results of the book.

The book covers the latest theoretical results and sophisticated applications in the field of variable-structure systems and sliding-mode control. This book is divided into four parts. Part I discusses new higher-order sliding-mode algorithms, including new homogeneous controllers and differentiators. Part II then explores properties of continuous sliding-mode algorithms, such as saturated feedback control, reaching time, and orbital stability. Part III is focused on the usage of variable-structure systems (VSS) controllers for solving other control problems, for example unmatched disturbances. Finally, Part IV discusses applications of VSS; these include applications within power electronics and vehicle platooning. Variable-structure Systems and Sliding-Mode Control will be of interest to academic researchers, students and practising engineers.

Production engineering and management involve a series of planning and control activities in a production system. A production system can be as small as a shop with only one machine or as big as a global operation including many manufacturing plants, distribution centers, and retail locations in multiple continents. The product of a production system can also vary in complexity based on the material used, technology employed, etc. Every product, whether a pencil or an airplane, is produced in a system which depends on good management to be successful. Production management has been at the center of industrial engineering and management science disciplines since the industrial revolution. The tools and techniques of production management have been so successful that they have been adopted to various service industries, as well. The book is intended to be a valuable resource to undergraduate and graduate students interested in the applications of production management under fuzziness. The chapters represent all areas of production management and are organized to reflect the natural order of production management tasks. In all chapters, special attention is given to applicability and wherever possible, numerical examples are presented. While the reader is expected to have a fairly good understanding of the fuzzy logic, the book provides the necessary notation and preliminary knowledge needed in each chapter.

This book presents methodological and application research in detecting cellular and molecular biophysical properties based on atomic force microscopy (AFM) nanorobotics. Series methods for in situ label-free visualizing and quantifying the multiple physical properties of single cells and single molecules were developed, including immobilization strategies for observing fine structures of living cells, measurements of single-cell mechanics, force recognition of molecular interactions, and mapping protein organizations on cell surface. The biomedical applications of these methods in clinical lymphoma treatments were explored in detail, including primary sample preparation, cancer cell recognition, AFM detection and data analysis. Future directions about the biomedical applications of AFM are also given.