Bøger i Studies in Systems, Decision and Control serien

This book offers insight into the current issues of the merger between reliability engineering and computational intelligence. The intense development of information technology allows for designing more complex systems as well as creating more detailed models of real-world systems which forces traditional reliability engineering approaches based on Boolean algebra, probability theory, and statistics to embrace the world of data science. The works deal with methodological developments as well as applications in the development of safe and reliable systems in various kinds of distribution networks, in the development of highly reliable healthcare systems, in finding weaknesses in systems with the human factor, or in reliability analysis of large information systems and other software solutions. In this book, experts from various fields of reliability engineering and computational intelligence present their view on the risks, the opportunities and the synergy between reliability engineering and computational intelligence that have been developed separately but in recent years have found a way to each other. The topics addressed include the latest advances in computing technology to improve the real lives of millions of people by increasing safety and reliability of various types of real-life systems by increasing the availability of software services, reducing the accident rate of means of transport, developing high reliable patient-specific health care, or generally, save cost and increase efficiency in the work and living environment. Though this book, the reader has access to professionals and researchers in the fields of reliability engineering and computational intelligence that share their experience in merging the two as well as an insight into the latest methods, concerns and application domains.

The book addresses a relevant field of digital processing and measurement of signals in distribution networks. The importance of the covered topic is evidenced by extensive foreign and domestic professional literature, in the form of publications in leading international journals, and numerous professional and scientific books. For the past two decades, the author has published a number of papers both in international journals and at leading world conferences, further verifying the results he has achieved in this field. It should be noted that he is also the holder of several national patents, which were created precisely as a result of working on the problems of processing complex signals of voltage and current. Readers of this book will be the students of master and doctoral studies both in the country and abroad and experts in the field of signal processing. It is a valuable source for future authors of professional and scientific papers, as a basis on which to start when developing completely new techniques for processing complex signals not only in the power system, but also in other fields of engineering and everyday life.

This book explores how AI is transforming digital marketing and what it means for businesses of all sizes and looks at how AI is being used to personalize content, improve targeting, and optimize campaigns. This book also examines some of the ethical considerations that come with using AI in marketing.

The book is devoted to the solution of the problem of determining the presence of corona discharge on electrical equipment with acoustic radiation. It is shown that corona discharge leads not only to irreversible losses of electrical energy, but also interferes with the transmission of high-frequency signals, deteriorates insulating elements, can become a source of conditions for the occurrence of a destructive arc discharge and is one of the factors of changing the continuity of the electrical system as a whole. The book describes the processes in a corona discharge that lead to the occurrence of acoustic waves. The authors analyzed acoustic radiation from a corona discharge reproduced in laboratory conditions. The received acoustic signals were processed by Fourier transform. Thus, the features of the spectral function, which belong specifically to the corona discharge in electrical networks with industrial frequency current, were determined. Based on the inverse Fourier transform, a simplified model of the acoustic radiation of the corona discharge was constructed. The authors proposed a method for detecting the presence of a corona discharge based on the spectral characteristics of acoustic radiation. Techniques were developed to determine the presence of a corona discharge for the creation of stationary and mobile devices. The advantages of the method of detecting the presence of corona discharge by the acoustic spectrum are shown. The method makes it possible to determine the presence of a corona discharge remotely, even out of direct sight, regardless of the time of day and regardless of the season. The book states that determining the presence of a corona discharge is not enough, it is still necessary to determine its location. The method of finding the coordinates of the corona discharge as a source of sound was described. Methods of searching for corona discharge coordinates with a fixed scanning device and a moving scanning device are proposed. A UAV is proposed as a mobile platform for the scanning system. The influence of the Doppler effect on acoustic measurements when the UAV speed changes was taken into account. The authors have shown that the use of coronal discharge detection with UAVs will not only enable the prevention of coronal discharge, but also increase the frequency of surface inspections. This will allow timely measures to be taken to improve the reliability of the power system operation. The book is intended for the researchers, postgraduate students and students specialized in theory and calculations of electrical systems.

This book presents the separation principle which is also known as the principle of separation of estimation and control and states that, under certain assumptions, the problem of designing an optimal feedback controller for a stochastic system can be solved by designing an optimal observer for the system's state, which feeds into an optimal deterministic controller for the system. Thus, the problem may be divided into two halves, which simplifies its design. In the context of deterministic linear systems, the first instance of this principle is that if a stable observer and stable state feedback are built for a linear time-invariant system (LTI system hereafter), then the combined observer and feedback are stable. The separation principle does not true for nonlinear systems in general. Another instance of the separation principle occurs in the context of linear stochastic systems, namely that an optimum state feedback controller intended to minimize a quadratic cost is optimal forthe stochastic control problem with output measurements. The ideal solution consists of a Kalman filter and a linear-quadratic regulator when both process and observation noise are Gaussian. The term for this is linear-quadratic-Gaussian control. More generally, given acceptable conditions and when the noise is a martingale (with potential leaps), a separation principle, also known as the separation principle in stochastic control, applies when the noise is a martingale (with possible jumps).

This book proposes analysis and design techniques for Markov jump systems (MJSs) using Lyapunov function and sliding mode control techniques. It covers a range of topics including stochastic stability, finite-time boundedness, actuator-fault problem, bumpless transfer scheme, and adaptive sliding mode fault-tolerant control for uncertain MJSs. Notably, the book presents a new model for deception attacks (DAs), establishing the correlation between attacks and time delays, which should be of particular interest due to the recent increase in such attacks. The book's content is presented in a comprehensive, progressive manner, with fundamental principles introduced first before addressing more advanced techniques. The book features illustrations and tables, providing readers with a practical and intuitive approach to applying these methods in their own research. This book will prove invaluable to researchers and graduate students in control engineering and applied mathematics with an interest in the latest developments in MJSs.

This book proposes a solution to the problem of incorrect use of automation tools to perform complex design work.Currently, a large number of start-up projects are non-professional design bureaus that show a huge amount of their achievements. In reality, most of these achievements burst like soap bubbles. This is due to the low-quality and inefficient use of information technology in this industry.The book highlights advanced information technologies in the fields of design, machine learning, and computer vision.

This book covers vibroacoustic monitoring, inertial attitude systems, and control system for device processing in complex objects. Modern approaches to the synthesis of algorithmic support for a strapdown inertial attitude system are considered. The general characteristics of navigation systems and the composition of their inertial measurement unit are given. The methods of initial alignment of the system on a stationary base are described. Particular attention is paid to the attitude kinematic parameters of the body frame and methods of their numerical integration. Picard's methods for integrating the Bortz and Poisson kinematic equations are shown. An algorithm for a strapdown inertial attitude system based on using real signals of high-precision laser gyroscopes is proposed. System simulation was carried out using the proposed algorithmic methods.The relevance of the control system created for the processing device parts in the conditions of automated manufacturing is substantiated. Theoretical studies are presented, and the relation between electrical signals, the level of tool wear, and the main reasons for generating electrical signals are identified. A mathematical model of cutting tool wear control was developed based on measuring the variable component of cutting electromotive force. A control system for processing device parts on computer numerical control machines in automated production conditions has been developed. It allows for recording critical wear and breakage of the cutting tool, performing its dimensional adjustment directly on the device, and carrying out its industrial approval in flexible production systems.

This book covers new technologies and methods related to models for short-term forecasting of electricity imbalances in the IPS of Ukraine, taking into account the impact of forecasts of energy production from renewable sources on the accuracy of the imbalance forecast. The book proposed architecture and mathematical model of an artificial neural network for deep learning forecasting of short-term electricity imbalances using hourly data. Using a model to aggregate data with an hourly resolution followed by forecasting to reduce forecast error, the quasi-dynamic modeling method was used to analyze the impact of periodic generation on the network. The application of quasi-dynamic modeling also allows taking into account the system load curve, generation profile, storage system, as well as renewable energy sources (RES) operation in this area. The use of models makes it possible to achieve realistic estimates of generation for the required period. The book considers a local hybrid renewable energy system (HRES) based on different types of RES, which is more efficient than a system with one type of source.

This monograph studies the synchronization control of Markovian complex neural networks with time-varying delays, and the structure of the book is summarized as follows. Chapter 1 introduces the system description and some background knowledges, and also addresses the motivations of this monograph. In Chapter 2, the stochastic synchronization issue of Markovian coupled neural networks with partially unknown transition rates and random coupling strengths is investigated. In Chapter 3, the local synchronization issue of Markovian neutral complex networks with partially information of transition rates is investigated. The new delay-dependent synchronization criteria in terms of LMIs are derived, which depends on the upper and lower bounds of the delays. In Chapter 4, the local synchronization issue of Markovian nonlinear coupled neural networks with uncertain and partially unknown transition rates is investigated. The less conservative local synchronization criteria containing the bounds of delay and delay derivative are obtained based on the novel augmented Lyapunov-Krasovskii functional and a new integral inequality. In Chapter 5, the sampled-data synchronization issue of delayed complex networks with aperiodic sampling interval is investigated based on enhanced input delay approach, which makes full use of the upper bound of the variable sampling interval and the sawtooth structure information of varying input delay. In Chapter 6, the sampled-data synchronization issue of Markovian coupled neural networks with mode-dependent interval time-varying delays and aperiodic sampling intervals is investigated based on an enhanced input delay approach. Furthermore, the mode-dependent sampled-data controllers are proposed based on the delay dependent synchronization criteria. In Chapter 7, the synchronization issue of inertial neural networks with time-varying delays and generally Markovian jumping is investigated. In Chapter 8, we conclude the monograph by briefly summarizing the main theoretical findings.

The book is composed of 15 chapters in total. All chapters presented by the authors (co-authors) are published in the author¿s edition and aim to present an issue on how to achieve more sustainable and more environmentally safe development of modern transport and energy sector. The chapters are grouped into 3 parts. The first part ¿Decisions for alternative energy sources use in modern transport¿ represents novel solutions in alternative energy sources development and implementation in different spheres of the modern transport sector. The second part ¿Solutions for reducing negative impact of energy and transport on environment¿ is devoted to advances in technologies aimed on reducing impact of energy and transport sectors on environment and utilization of waste. The third part of the book ¿Advance in alternative motor fuels technology¿ represents recent developments in chemical technology of alternative fuels production and aspects of modern fuels quality control.

This book considers a class of ergodic finite controllable Markov's chains. The main idea behind the method, described in this book, is to develop the original discrete optimization problems (or game models) in the space of randomized formulations, where the variables stand in for the distributions (mixed strategies or preferences) of the original discrete (pure) strategies in the use. The following suppositions are made: a finite state space, a limited action space, continuity of the probabilities and rewards associated with the actions, and a necessity for accessibility. These hypotheses lead to the existence of an optimal policy. The best course of action is always stationary. It is either simple (i.e., nonrandomized stationary) or composed of two nonrandomized policies, which is equivalent to randomly selecting one of two simple policies throughout each epoch by tossing a biased coin. As a bonus, the optimization procedure just has to repeatedly solve the time-average dynamic programming equation, making it theoretically feasible to choose the optimum course of action under the global restriction. In the ergodic cases the state distributions, generated by the corresponding transition equations, exponentially quickly converge to their stationary (final) values. This makes it possible to employ all widely used optimization methods (such as Gradient-like procedures, Extra-proximal method, Lagrange's multipliers, Tikhonov's regularization), including the related numerical techniques. In the book we tackle different problems and theoretical Markov models like controllable and ergodic Markov chains, multi-objective Pareto front solutions, partially observable Markov chains, continuous-time Markov chains, Nash equilibrium and Stackelberg equilibrium, Lyapunov-like function in Markov chains, Best-reply strategy, Bayesian incentive-compatible mechanisms, Bayesian Partially Observable Markov Games, bargaining solutions for Nash and Kalai-Smorodinsky formulations, multi-traffic signal-control synchronization problem, Rubinstein's non-cooperative bargaining solutions, the transfer pricing problem as bargaining.

This book keeps an eye in the direction of applications of advanced and high performance scientific computing in describing the behavior of natural and constructed systems, e.g. chaos, bifurcation, fractal, Lyapunov exponent, period doubling, Poincaré map, strange attractor etc. With the aid of powerful computers the modem theory of chaos and its geometry, the fractals, and attractors are developed. The concepts of object oriented computing are introduced early in the text and steadily expanded as one progresses through the chapters. The beginning of each chapter is of an introductory nature, followed by practical applications, the discussion of numerical results, theoretical investigations on nonlinear stability and convergence.This is the first complete introduction to process modelling and computing that fully integrates software tools ¿ enabling professionals and students to master critical techniques hands on through computer simulations based on the popular MATLAB environment. The book offers a simple tool for all those oscillations that are travelling through the world, helping them discover its hidden beauty.Many applications as well as results of computer simulations are presented. The center of concern is set on existing as well as emerging continuous methods of investigations useful for researchers, engineers and practitioners active in many and often interdisciplinary fields, where physics, electrochemistry, biology and medicine play a key role. Coverage includes:¿ Dynamic behavior of nonlinear systems,¿ Fundamental descriptions of processes exhibiting nonlinear oscillations,¿ Mechanism and function of structures of nonlinear oscillations¿ patterns,¿ Analysis of dynamical oscillations in electric circuits and systems,¿ Artificial intelligence models of natural systems,¿ Nonlinear oscillations in chemistry, biologyand medicine,¿ Oscillations in mechanics and transport systems,¿ Oscillations in fractional-order systems,¿ Energy harvesting systems from the surrounding environment.With an insatiable appetite for exploring the surrounding world and doing research, this book can help readers quickly find ways to use new computers and facilitate the quest for greater knowledge and understanding of reality. The reach of novelty of the book ranges from new mathematical ideas to motivating questions and science issues in many subject areas.

This book chooses the topic which is due to the editors' experience in modeling projects in healthcare systems. Also, the transfer of experiences is the reason why mathematical modeling and decision making in the field of health are not given much attention. To this end, the new aspect of this book is the lack of reference needed to carry out projects in the field of health for researchers whose main expertise is not modeling. Students of health, mathematics, management, and industrial engineering fields are in the direct readership with this book. Different projects in the field of healthcare systems can use the topics presented in different chapters mentioned in this book.

Presently, we stand on the threshold of a technological revolution that will drastically change the way we live, work, and communicate with each other. By the current rate, scope, and complexity, this transformation will be as fundamental for society as any other technological paradigm change from the past. The industries which are more susceptible to change are technologically oriented industries including banking, finance, accounting, and auditing. One of the technological concepts of the technological revolution is the concept of the digital twin.The application of digital twins and AI as paired with Internet of Things technologies makes it possible to solve ESG problems on a completely different level (Li, 2019) for accounting firms and financial institutions. These include recycling on demand, rational energy consumption, smart surveillance cameras for crime tracking, and smart branch parking solutions, monitoring the wear and tear and conditions of financial technology infrastructures.Moreover, numerous researchers and practitioners emphasize the significance of innovating sustainable business models and operations (Geissdoerfer et al., 2018). The digital twin will allow businesses and financial institutions to minimize costs, boost customer service, and find new ways to generate revenue. DTW is accessible now more than ever, and many reputable and innovative companies such as Tesla, Ericsson, and Siemens have adopted it with varying success.Therefore, this book examines the opportunities, challenges, and risks of artificial intelligence-augmented digital twins for financial operations, innovation, and sustainable development. It focuses on AI and digital twin technologies to furnish solutions for the current industrial revolution including the Metaverse. Henceforth, this book aims to encourage authors to submit multi-disciplinary chapters indicating the current scholarly challenges about the applications and potential of artificial intelligence and digital twins in accounting, finance, and banking.

This book aims to work out the distributed economic operation in smart grids in a systematic way, which ranges from model-based to model-free perspectives. The main contributions of this book can be summarized into three folds. First, we investigate the fundamental economic operation problems in smart grids from model-based perspective. Specifically, these problems can be modeled as deterministic optimization models, and we propose some distributed optimization algorithms by integrating the multi-agent consensus theory and optimization techniques to achieve the distributed coordination of various generation units and loads. Second, due to the randomness of the large-scale renewable energies and the flexibility of the loads, we further address these economic operation problems from a model-free perspective, and we propose learning-based approaches to address the uncertainty and randomness. At last, we extend the idea of model-based and model-free algorithms to plug-in electric vehicles (PEVs) charging/discharging scheduling problem, the key challenge of which involves multiple objectives simultaneously while the behavior of PEVs and the electricity price are intrinsically random. This book presents several recent theoretical findings on distributed economic operation in smart grids from model-based and model-free perspectives. By systematically integrating novel ideas, fresh insights, and rigorous results, this book provides a base for further theoretical research on distributed economic operation in smart grids. It can be a reference for graduates and researchers to study the operation and management in smart grids. Some prerequisites for reading this book include optimization theory, matrix theory, game theory, reinforcement learning, etc.

This book presents several robust sliding mode protocols for achieving the formation and tracking of Quadcopter swarm for a given pattern. In entire book, the concept of leader-follower formation control of a multi-agent system is exploited for deriving the protocols and the graph theory is used to represent the communication between the Quadcopters. The book covers two types of formation protocols of the Quadcopter swarm namely, continuous-time sliding mode protocols and discrete-time sliding mode protocols. First, the continuous-time higher order sliding mode protocols using super-twisting algorithm are designed for formation using linear and non-linear models of Quadcopter. Then, the discrete-time sliding mode protocols using power rate reaching law, discrete-time super twisting algorithm, and exponential reaching law are presented. The protocols are thoroughly analysed for robustness, chattering, control effort, and convergence time for achieving the formation. Also, the stability conditions using the Lyapunov function are derived to ensure the stability of the swarm with each protocol. Further, each chapter includes extensive simulation and comparative studies to show the efficacy of each protocol. The book will be useful to graduate students, research scholars, and professionals working in the domain of civilian and military usage of the drone technology.

Moreover, because adaptive networks are described in a network format as well, the approach can simply be applied iteratively, so that higher-order adaptive networks in which network adaptation itself is adaptive (second-order adaptation), too can be modeled just as easily.