Bøger i Studies in Systems, Decision and Control serien

The book consists of recent works on several axes either with a more theoretical nature or with a focus on applications, which will span a variety of up-to-date topics in the field of systems and control.The main market area of the contributions include:Advanced fault-tolerant control, control reconfiguration, health monitoring techniques for industrial systems, data-driven diagnosis methods, process supervision, diagnosis and control of discrete-event systems, maintenance and repair strategies, statistical methods for fault diagnosis, reliability and safety of industrial systems artificial intelligence methods for control and diagnosis, health-aware control design strategies, advanced control approaches, deep learning-based methods for control and diagnosis, reinforcement learning-based approaches for advanced control, diagnosis and prognosis techniques applied to industrial problems, Industry 4.0 as well as instrumentation and sensors. These works constitute advances in the aforementioned scientific fields and will be used by graduate as well as doctoral students along with established researchers to update themselves with the state of the art and recent advances in their respective fields. As the book includes several applicative studies with several multi-disciplinary contributions (deep learning, reinforcement learning, model-based/data-based control etc.), the book proves to be equally useful for the practitioners as well industrial professionals.

This book overviews latest ideas and developments in financial econometrics, with an emphasis on how to best use prior knowledge (e.g., Bayesian way) and how to best use successful data processing techniques from other application areas (e.g., from quantum physics). The book also covers applications to economy-related phenomena ranging from traditionally analyzed phenomena such as manufacturing, food industry, and taxes, to newer-to-analyze phenomena such as cryptocurrencies, influencer marketing, COVID-19 pandemic, financial fraud detection, corruption, and shadow economy. This book will inspire practitioners to learn how to apply state-of-the-art Bayesian, quantum, and related techniques to economic and financial problems and inspire researchers to further improve the existing techniques and come up with new techniques for studying economic and financial phenomena. The book will also be of interest to students interested in latest ideas and results.

This book presents the theory and application of the models presented in this regard and establishes a meaningful relationship between data envelopment analysis and multi-attribute decision making. The issue of "choice" using the aggregation of voters' votes is one of the most important group decision-making issues that are always considered by decision makers in electoral systems. Voting is a method of group decision making in a democratic society that expresses the will of the majority. Voting is perhaps the simplest way to gather the opinions of experts, and this ease of application has made it a multi-attribute decision-making method in group decisions. Preferential voting is a type of voting that may refer to electoral systems or groups of the electoral system. In preferential voting, voters vote for multiple candidates, and how the candidates are arranged on the ballot is important. Researchers have made many efforts to provide models of voter aggregation, and one of the bestresults of these efforts is the aggregation of votes based on the policy of data envelopment analysis. Thus, in group decisions, the opinions of experts are obtained in a simple structure and consolidated in an interactive and logical structure, and the results can be a powerful tool for decision support.This book provides a complete set of voting models based on data envelopment analysis and expressing its various applications in industry and society. However, most decision-making methods do not use the opinions of experts or reduce the motivation of experts to participate in complex interactions and time, while voting methods do not have this shortcoming.This book is suitable for graduate students in the fields of industrial management, business management, industrial engineering, applied mathematics, and economics. It can also be a good source for researchers in decision science, decision support systems, data envelopment analysis, supply chain management, healthcare management, and others. The methods presented in this book can not only offer a comprehensive framework for solving the problems of these areas but also can inspire researchers to pursue new innovative hybrid methods.

The book presents recent applications and developments in the field of control of industrial systems, covering a wide range of modeling and feedback control using various robust approaches such as fuzzy systems, sliding mode control, and H-infinity. This book provides insights into theory, applications, and perspectives relevant to the field of robotic systems, exoskeletons, power systems, photovoltaic systems, etc., as well as general methodologies and paradigms around them. Each chapter provides an enriched understanding of a research topic along with a balanced treatment of the relevant theories, methods, or applications. It reports on the latest advances in the field. This book is a good reference for graduate students, researchers, educators, engineers, and scientists and contains a total of 15 chapters divided into five parts as follows. The first part of this book focuses on the application of fuzzy control to robotic systems and consists of threechapters. The second part of this book proposes the control of lower and upper limb exoskeletons and includes two chapters. The third part is dedicated to the control of power systems and comprises three chapters. The fourth part deals with various approaches to the modeling and control of industrial processes and comprises four chapters. The fifth and final part describes observers and fault-tolerant control systems and comprises five chapters.

This book presents generalized Caputo fractional Ostrowski and Grüss-type inequalities involving several Banach algebra valued functions. Furthermore, the author gives generalized Canavati fractional Ostrowski, Opial, Grüss, and Hilbert-Pachpatte-type inequalities for multiple Banach algebra valued functions. By applying the p-Schatten norms over the von Neumann¿Schatten classes, the author produces the analogous refined and interesting inequalities. The author provides many applications. This book¿s results are expected to find applications in many areas of pure and applied mathematics, especially in fractional inequalities and fractional differential equations. Other interesting applications are in applied sciences like geophysics, physics, chemistry, economics, and engineering. This book is appropriate for researchers, graduate students, practitioners, and seminars of the above disciplines, also to be in all science and engineering libraries.

This book provides a systematic framework to enhance the ability of complex dynamical systems in risk identification, security assessment, system protection, and recovery with the assistance of advanced control and optimization technologies. By treating external disturbances as control inputs, optimal control approach is employed to identify disruptive disturbances, and online security assessment is conducted with Gaussian process and converse Lyapunov function. Model predictive approach and distributed optimization strategy are adopted to protect the complex system against critical contingencies. Moreover, the reinforcement learning method ensures the efficient restoration of complex systems from severe disruptions. This book is meant to be read and studied by researchers and graduates. It offers unique insights and practical methodology into designing and analyzing complex dynamical systems for resilience elevation.

This book presents the main results of the 19th Latin American Congress of Automatic Control held in November 2022 in Havana, Cuba. The Congress showed several main research results obtained by researchers from diverse countries in the last four years.Of the papers sent to Congress, 28 were finally accepted for presentation after a rigorous analysis of scientific novelty and quality. For their presentation in this book, the papers were divided into 5 major sections that appear in the following order:Part 1. Robust and Nonlinear ControlThe main research topics addressed in this part are related to fault-tolerant control loops, control by sliding modes, and robust tuning of PID controllers. Examples of electrical motors and chemical processes are used to demonstrate the feasibility of using the proposed techniques.Part 2. Fault Diagnosis in Industrial SystemsFault diagnosis in industrial plants is a very important topic in the Industry 4.0 paradigm.In this part, new techniques of fault diagnosis in mechanical systems using Poincaré features; a real case study for predicting the time of the remaining job cycle at a water treatment plant; and a predictive fault diagnosis for isolated photovoltaic systems are presented. A novel methodology for detecting and locating cyber-attacks in water distribution networks using computational intelligence tools is also presented.Part 3. Robotic and Autonomous SystemsNew control strategies for path following for autonomous tractors and unmanned aquatic vehicles are analyzed in this part. Moreover, the important topic related to the battery health-aware model predictive control planning for autonomous racing vehicles and the use of robots for monitoring and remediation applications are examined.Part 4. Modeling, Identification, and Delayed SystemsA model-based methodology for the efficient selection of centrifugal pumps; the use of probabilistic Boolean networks in smart grid models; the utilization of PSO metaheuristic algorithm in the selection of a model structure; and two schemes to control high-order delayed systems are among the main topics examined in this part.Part 5. Low-Cost Systems and Biomedical ApplicationsIn this part, some applications of low-cost monitoring and control systems and two automatic systems used for the characterization of creatinine in wastes samples during hemodialysis process and differential acquisition of blood pressure are shown.

Communication-Protocol-Based Filtering and Control of Networked Systems is a self-contained treatment of the state of the art in communication-protocol-based filtering and control; recent advances in networked systems; and the potential for application in sensor networks. This book provides new concepts, new models and new methodologies with practical significance in control engineering and signal processing. The book first establishes signal-transmission models subject to different communication protocols and then develops new filter design techniques based on those models and preset requirements for filtering performance. The authors then extend this work to finite-horizon H-infinity control, ultimately bounded control and finite-horizon consensus control. The focus throughout is on three typical communications protocols: the round-robin, random-access and try-once-and-discard protocols, and the systems studied are drawn from a variety of classes, among them nonlinear systems, time-delayed and time-varying systems, multi-agent systems and complex networks.Readers are shown the latest techniques-recursive linear matrix inequalities, backward recursive difference equations, stochastic analysis and mapping methods. The unified framework for communication-protocol-based filtering and control for different networked systems established in the book will be of interest to academic researchers and practicing engineers working with communications and other signal-processing systems. Senior undergraduate and graduate students looking to increase their knowledge of current methods in control and signal processing of networked systems will also find this book valuable.

This book reviews and presents several advanced approaches to energy infrastructure assets' intelligent reliability and maintainability. Each introduced model provides case studies indicating high efficiency, robustness, and applicability, allowing readers to utilize them in their understudy intelligent reliability and maintainability of energy infrastructure assets domains.The book begins by reviewing the state-of-the-art research on the reliability and maintainability of energy infrastructure assets and emphasizes the intelligent tools and methods proposed from a bibliometric and literature review point of view. It then progresses logically, dedicating a chapter to each approach, dynamic Bayesian modeling network, convolutional neural network model, global average pooling-based convolutional Siamese network, an integrated probabilistic model for the failure consequence assessment, and more.This book interests professionals and researchers working in reliability and maintainability and postgraduate and undergraduate students studying intelligent reliability applications and energy infrastructure assets' maintainability.

This book is concerned with the development of the understanding of the relational structures of information, knowledge, decision¿choice processes of problems and solutions in the theory and practice regarding diversity and unity principles of knowing, science, non-science, and information¿knowledge systems through dualistic-polar conditions of variety existence and nonexistence. It is a continuation of the sequence of my epistemic works on the theories on fuzzy rationality, info-statics, info-dynamics, entropy, and their relational connectivity to information, language, knowing, knowledge, cognitive practices relative to variety identification¿problem¿solution dualities, variety transformation¿problem¿solution dualities, and variety certainty¿uncertainty principle in all areas of knowing and human actions regarding general social transformations. It is also an economic¿theoretic approach in understanding the diversity and unity of knowing and science through neuro-decision¿choice actions over the space of problem¿solution dualities and polarities. The problem¿solution dualities are argued to connect all areas of knowing including science and non-science, social science, and non-social-science into unity with diversities under neuro-decision¿choice actions to support human existence and nonexistence over the space of static¿dynamic dualities. The concepts of diversity and unity are defined and explicated to connect to the tactics and strategies of decision¿choice actions over the space of problem¿solution dualities. The concepts of problem and solution are defined and explicated not in the space of absoluteness but rather in the space of relativity based on real cost¿benefit conditions which are shown to be connected to the general parent¿offspring infinite process, where every solution generates new problem(s) which then generates a search for new solutions within the space of minimum¿maximum dualities in the decision¿choice space under the principle of non-satiation over the space of preference¿non-preference dualities with analytical tools drawn from the fuzzy paradigm of thought which connects the conditions of the principle of opposites to the conditions of neuro-decision¿choice actions in the zone of variety identifications and transformations. The Monograph would be useful to all areas of Research, Learning and Teaching at Advanced Stages of Knowing and Knowledge Production.

This book is based on the accepted research papers presented in the International Conference "Artificial Intelligence in Engineering & Science" (AIES-2022). The aim of the AIES Conference is to bring together researchers involved in the theory of computational intelligence, knowledge engineering, fuzzy systems, soft computing, machine learning and related areas and applications in engineering, bioinformatics, industry, medicine, energy, smart city, social spheres and other areas. This book presents new perspective research results: models, methods, algorithms and applications in the field of Artificial Intelligence (AI). Particular emphasis is given to the medical applications - medical images recognition, development of the expert systems which could be interesting for the AI researchers as well for the physicians looking for the new ideas in medicine. The central audience of the book are researchers, industrial practitioners, students specialized in the Artificial Intelligence.

This book discusses incentives for information management, usage of information for existing practices to become more efficient, the acceleration of executive learning, and an evaluation of the information management impact on an organization. In today's COVID-influenced volatile world, companies face a variety of challenges. And the most crucial of them are high levels of uncertainty and risk. Therefore, companies are constantly under pressure to provide sustainable solutions. Accordingly, previously gathered knowledge and information can be extremely helpful for this purpose. Hence, this fourth book of our subseries continues to accentuate on different approaches, which point to the importance of continuous progress in structural management for sustainable growth. It highlights the permanent gain and usage of information. We would be pleased if the book can stimulate further research on this subject matter.

This book presents the latest achievements in the field of theory and practice of information processing in the CNS SEMS. Recently, the task of integrating computer technologies, transmitting and storing information, monitoring and controlling objects of the physical world has become urgent. This capability is provided by Smart Electromechanical Systems (SEMS) used in Cyber-Physical Systems (CPhS). The main tasks in the field of theory and practice of SEMS are to ensure the efficiency, reliability and safety of functioning in real time. The task of obtaining reliable information about the selection environment, as well as object recognition and identification, is especially important when several SEMS interact in a group. Since in this case, it is necessary to ensure the safety and speed of the planned behavior of all members of the group.The purpose of the publication is to familiarize with the latest achievements of scientists of the Russian Academy of Sciences and leading universities of Russia in the field of theory and practice of information processing in the CNS of EMS, as well as to familiarize with the development of methods and algorithms for recognition, identification and modeling based on the principles of bionics, adaptivity, intelligence and parallelism in information processing and computing.Topics of primary interest include, but are not limited to the following:  Methods and systems of recognition and identification;Mathematical and computer modeling; Measurement systems to identify the simulation of the selection environment;Sensors and auxiliary SEMS systems.This book is intended for students, scientists and engineers specializing in smart electromechanical systems and robotics.

This book is a timely book to summarize the latest developments in the optimization of tuned mass dampers covering all classical approaches and new trends including metaheuristic algorithms. Also, artificial intelligence and machine learning methods are included to predict optimum results by skipping long optimization processes. Another difference and advantage of the book are to provide chapters about several types of control types including passive tuned mass dampers, active tuned mass dampers, tuned liquid dampers, tuned liquid column dampers and inerter dampers. Tuned mass dampers (TMDs) are vibration absorber devices used in all types of mechanic systems. The key factor in the design is an effective tuning of TMDs for the desired performance. In practice, several high-rise structures and bridges were designed by including TMDs. Also, TMDs were installed after the construction of the structures after several negative experiences resulting from the disturbing sway of the structures. In optimum design, several closed-form expressions have been proposed for optimum frequency and damping ratio of TMDs, but the exact optimization requires iterative optimization approaches. The current trend is to use evolutionary algorithms and metaheuristic optimization methods to reach the goal.

This book focuses on the impact of artificial intelligence (AI) and machine learning (ML) models on supply chain operations in industry 4.0. The chapters illustrate the AI and ML models for all functional areas of operations in SCM. The book also includes examples using ML models like handling supply-to-demand imbalances, triggering automated responses, and reinforcing customer relationships. It describes the evolution of blockchain technology coupled with the ability to automate business logic for the transparency of goods, infrastructure, products, and licenses in software. The book also includes case studies that provide a problem statement and industry overcome by applying ML and AI technologies. This book is suitable for undergraduates, postgraduates, industrial professionals, business executives, entrepreneurs, and freelancers to encourage practical learning on AI and ML algorithms in SCM 4.0. Additionally, this book will provide computer science and information system professionals with the latest technologies embedded in the corporate world.

This book shows how a conventional multi-layered approach can be used to control a snake robot on a desired path while moving on a flat surface. To achieve robustness to unknown variations in surface conditions, it explores various adaptive robust control methods.The authors propose a sliding-mode control approach designed to achieve robust maneuvering for bounded uncertainty with a known upper bound. The control is modified by addition of an adaptation law to alleviate the overestimation problem of the switching gain as well as to circumvent the requirement for knowledge regarding the bounds of uncertainty. The book works toward non-conservativeness, achieving efficient tracking in the presence of slowly varying uncertainties with a specially designed framework for time-delayed control. It shows readers how to extract superior performance from their snake robots with an approach that allows robustness toward bounded time-delayed estimation errors. The book also demonstrates how the multi-layered control framework can be simplified by employing differential flatness for such a system. Finally, the mathematical model of a snake robot moving inside a uniform channel using only side-wall contact is discussed. The model has further been employed to demonstrate adaptive robust control design for such a motion.Using numerous illustrations and tables, Adaptive Robust Control for Planar Snake Robots will interest researchers, practicing engineers and postgraduate students working in the field of robotics and control systems.

This book aims to systematically review and design different intelligent control algorithms for the small-signal stability assessment of HPS. With the growing consciousness of global warming and the fast depletion of natural power generation resources, the existing power system is on the verge of transitions to a "hybrid power system (HPS)" integrated with distributed energy resources. The recent results and requirements for the developments of intelligent control algorithms have motivated the authors to introduce this book for extensively analyzing the performance of HPS against unknown/uncertain disturbances. This book introduces fractional-order resilient control methodologies for arresting small-signal instability of HPS. The prospective investigation has been performed on the MATLAB platform. This book is helpful for undergraduate, postgraduate students, and research scholars working in power system stability, control applications, and soft computing in particular.

This book describes new techniques for making decisions in situations with uncertainty and new applications of decision-making techniques.The main emphasis is on situations when it is difficult to decrease uncertainty. For example, it is very difficult to accurately predict human economic behavior, so in economics, it is very important to take this uncertainty into account when making decisions. Other areas where it is difficult to decrease uncertainty are geosciences and teaching. The book analyzes the general problem of decision making and shows how its results can be applied to economics, geosciences, and teaching. Since all these applications involve computing, the book also shows how these results can be applied to computing, including deep learning and quantum computing.The book is recommended to researchers, practitioners, and students who want to learn more about decision making under uncertainty¿and who want to work on remaining challenges.

This book describes an original approach to solving tasks of individual and collective choice: classification, ranking, and selection of multi-attribute objects. Object representation with multisets allows considering simultaneously numerical and symbolic variables. In group verbal decision analysis, judgments of all participants are taken into account without a compromise between contradictory. Natural language is used to describe problems and objects, formalize knowledge of experts and preferences of decision makers, and explain results. Verbal methods and technologies are more transparent, less laborious for a person, and weakly sensitive to measurement errors. The book also includes examples of applying new tools in real ill-structured high-dimensional choice tasks. It is intended for researchers, managers, consultants, analysts, and developers as well as for teachers and students of applied mathematics, computer science, information processing, engineering, economics, and management.