Böcker i Studies in Systems, Decision and Control-serien

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.

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 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 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 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 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 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 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.

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 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.

From the start of life, people used their brains to make something better in design in ordinary works. Due to that, metaheuristics are essential to living things, and several inspirations from life have been used in the generation of new algorithms. These algorithms have unique features, but the usage of different features of different algorithms may give more effective optimum results in means of precision in optimum results, computational effort, and convergence. This book is a timely book to summarize the latest developments in the optimization of structural engineering systems covering all classical approaches and new trends including hybrids metaheuristic algorithms. Also, artificial intelligence and machine learning methods are included to predict optimum results by skipping long optimization processes. The main objective of this book is to introduce the fundamentals and current development of methods and their applications in structural engineering.

Although there is much literature on organisational learning, mathematical formalisation and computational simulation, there is no literature that uses mathematical modelling and simulation to represent and explore different facets of multilevel learning. This book provides an overview of recent work on mathematical formalisation and computational simulation of multilevel organisational learning by exploiting the possibilities of self-modeling network models to address it. This is the first book addressing mathematical formalisation and computational modeling of multilevel organisational learning in a systematic, principled manner. A self-modeling network modeling approach from AI and Network Science is used where in a reflective manner some of the network nodes (called self-model nodes) represent parts of the network¿s own network structure characteristics. This is supported by a dedicated software environment allowing to design and implement (higher-order) adaptive network models by specifying them in a conceptual manner at a high level of abstraction in a standard table format, without any need of algorithmic specification or programming. This modeling approach allows to model the development of knowledge in an organisational setting in a neatly structured manner at three different levels for the usage, adaptation and control, respectively, of the underlying mental models. Several examples of realistic cases of multilevel organisational learning are used to illustrate the approach. Crucial concepts such as the aggregation of mental models to form shared mental models out of individual mental models are addressed extensively. It is shown how to model context-sensitive control of organisational learning taking into account a wide variety of context factors, for example relating to levels of expertise of individuals or to leadership styles of managers involved. Mathematical equilibrium analysis of models of organisational learning is also addressed, among others allowing verification of correctness of the implemental models in comparison to their conceptual design. Chapters in this book also contribute to the Management and Business Sciences research by demonstrating how computational modeling can be used to capture complex management phenomena such as multilevel organizational learning. This book has a potential implication for practice by demonstrating how computational modeling can be used to capture learning scenarios, which then provide a basis for more informed managerial decisions.

Networked switched system has emerged as an essential system model in the field of control due to its accurate reflection of the wide-area distribution and typical switching characteristics of increasingly sophisticated controlled objects in engineering practice. The openness of communication networks, the limitation of communication resources, and the complexity of switching behaviors make it a challenging task to ensure the steady-state and transient performance of the output regulation of networked switched systems. This book proposes several novel methodologies for output regulation of networked switched systems from the perspective of both steady-state and transient performance. The core features of our approaches are fourfold: i) Without imposing stability requirements on individual subsystems and all switching instants, a series of innovative dwell-time switching technologies are established to handle the issue of output regulation for networked switched systems with severely unstable dynamics under event-triggering strategies in the presence of cyber attacks. ii) Taking into account switching rules and cyber attack parameters within the event-triggered control framework, event detection conditions, modal matching conditions, and event waiting conditions are constructed, and a series of new event-triggering mechanisms are proposed to effectively enhance network resource utilization and secure steady-state performance of networked switched systems. iii) Typical cyber attacks have unique consequences on the secure steady-state performance of networked switched systems with severely unstable dynamics due to the short activation time of a single subsystem and the necessity to relay the switching signal through the network. To this purpose, the consecutive asynchronous switching behaviors of the subsystem or controller resulting from a long-duration DoS attack or an integrity deception attack incorporating switching signal tampering are investigated. iv) To deal with the transient performance fluctuations of the closed-loop system caused by factors such as mismatch switching between the subsystem and the corresponding controller, data update at event-triggering instants, cyber attack blocking and tampering of transmitted data, etc., bumpless transfer control strategies are formulated in the interpolation type and multi-source type, balancing the transient and steady-state performances of the output regulation of networked switched systems. This book presents these topics in a systematic way, which is of tremendous importance to both theoretical research and practical applications involving switched systems.

The book aims to deal with the main advances in the study of artificial intelligence, the digital and circular economy, and innovation from a multidisciplinary perspective.Whoever governs the artificial intelligence will hold the keys to the world and the future. This book explains the growing role of artificial intelligence in our lives and the need to understand its mechanisms.The book presents original research articles addressing various aspects of artificial intelligence applied to economics, law, management, and optimization. The topics discussed include economics, territorial policies, law, resource allocation strategies, information technology, and learning for inclusion.Combining the input of contributing professors and researchers from Italian and other foreign universities, the book is of interest to students, researchers, and practitioners, as well as members of the public in general, interested in the world of the artificial intelligence and economics.

Advanced manufacturing via computer numerical machining is the art of producing mechanical components employed in aerospace, automobile, and industrial applications where a high level of accuracy is needed. This book focuses on the nano-machining of aluminum alloy and its optimization. The application of aluminum alloy in the manufacturing industry has increased tremendously due to its lightweight to high strength ratio and high-level resistance to corrosion. However, aluminum alloy has some challenges during the machining and manufacturing stage in order to solve real-life manufacturing challenges in advanced machining operation for sustainable production processes. Therefore, it is a need for the implementation of a general algebraic modeling system (GAMS) and other metaheuristic techniques for problem solving and to effectively develop mathematical models for high accuracy prediction and optimization under nano-lubrication machining conditions. This book discusses majorly on themajor three responses in machining such as surface roughness, cutting force, and material removal rate, which will give an excellent guide to undergraduate and postgraduate students, senior research fellows in academia, operational, and strategic staff in manufacturing industries.

This book is devoted to the study of engineering and control technologies for the cyber-physical systems development. This book defines the approaches in the engineering leverage the exploitation of artificial intelligence and most urgent computing methods. The authors study the activities allows for the developing new and perspective concepts of robotics systems combining various machine learning methods, uncertainty explanation approaches, computer vision and unmanned aerial systems control technologies including artificial neural networks and simulation modeling by addressing a large scale of applications. The book also describes new materials engineering as well as implementation of these technologies in the different domains such as polymeric film production, polymer composition, and roller squeezing of leather, in order to realize the novel cyber-physical systems, their functionalities, and features. The authors describe the development of method for increasing the software efficiency, considering the increasing complexity of the computing systems and the importance of ensuring accuracy and velocity of modelling. The book also analyses algorithms for fuzzy models and systems, including the cyber-physical real-time systems, and non-stationary object with discrete time. The authors highlight the problem of ensuring the quality on engineering technologies for cyber-physical systems as the most important and consider different approaches to its solution.

This book aims at bringing together global researchers to generate thought on how this transition from Industry 4.0 to Industry 5.0 could make a difference to the globe for larger good. The collaboration and interaction between man and machine has given rise to Industry 5.0. With the prime objective of Industry 5.0 to create a benefit for the human beings while tapping on to the advantage of Industry 4.0, in no case, does it replace what has already been achieved. In fact, it brings to light what can be done in order to make life better. While Industry 4.0 offered extraordinary technological advancement, Industry 5.0 reasons out that technology alone is not sufficient to answer everything or provide a solution, but it is an amalgamation of both machine and human interaction to create that difference. In fact, with the impact of widespread digitalization that has led to dehumanization of the industrial makeup, the interest of global researchers has increased toward mapping how the humancreativity and brainpower can be reconciled with the intelligent systems that can enhance process efficiency.Industry 5.0 has touched upon some of those key domains which are of much concern and debate globally including resilience (both business and cyber), environment and sustainability, diversity and inclusion, values and ethics, vision and purpose, circular economy, understanding the human¿machine collaboration and the ¿human-touch¿ in the production process.This transition that has taken place in moving from Industry 4.0 to Industry 5.0 has essentially created a need to pay cognizance to the role of ¿human¿ in the process which creates an enhanced focus toward the right kind of skills and competencies, identification of training and developmental needs, talent acquisition and management, safety and wellbeing, future of work as well as hybrid working models.Undeniably, the pace with which Industry 4.0 has been accelerating has bypassed the first three industrial revolutions, which is definitely a consequence of the fast introduction of new and cutting-edge technologies. While organizations are already in analyzing the context, mapping this transition and the flow of activities from Industry 4.0 to 5.0 is gaining attention as Industry 4.0 lacked personalization and customization. This co-existence of man and machine creates a pathway for newer prospects and opportunities to emerge and expand possibilities of personalization with the empowerment of ¿human¿ in the production process.This lays the foundation for this book. This book adopts a forward-looking approach by bringing in research and contributions that facilitate in mapping the consereasons, consequences and solutions for ¿man+machine¿ across industries. This book serves as a guide not just to academia but also to the industry to adopt suitable strategies that offer insights into global best practices as well as the innovations in the domain.

This book aims to familiarize with the basics of the SEMS theory, including logical-probabilistic and logical-linguistic methods for their design and modeling, taking into account the incomplete certainty of the operating environment and the mental characteristics of the members of the human¿machine systems collective. Smart electromechanical systems (SEMS) are used in cyber-physical systems (CPS). The main tasks in the field of theory and practice of CPS are to ensure the efficiency, reliability and safety of operation in real time.SEMS have been widely used since 2000 in parallel robots or so-called parallel kinematic machines. They offer good opportunities in terms of precision, rigidity and the ability to handle heavy loads. SEMS are used in unmanned vehicles, astronomy, machine tools, medicine and other fields.Currently, much attention is paid to the methods of designing and modeling SEMS based on the principles of adaptability, intelligence, biomorphism of parallel kinematics and parallelism in information processing and control calculations. The book consists of four parts:- Mechanisms and control systems;- The central nervous system;- Group control;- Examples of using SEMS modules.The book is recommended for specialists in the field of control, as well as a textbook for masters of universities specializing in the field of smart electromechanical systems and robotics and includes many scientific fields such as kinematics, dynamics and control theory.

The book consists of 8 parts: Energy Informatics, Electric Power Engineering, Heat Power Engineering, Nuclear Power Engineering, Renewable Power Engineering, Fuels, Transport, and Environmental Safety. The results presented in this book are aimed at solving some of the technical issues proposed by the Ukraine Recovery Plan and other important scientific and applied problems in the field of energy. Scientists from leading Ukrainian academic institutions and universities are working on this book.This book is for scientists, researchers, engineers, as well as lecturers and postgraduates of higher education institutions dealing with energy sector, power systems, ecological safety, etc.