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The book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in financial systems when these are described in the form of nonlinear ordinary differential equations. It then addresses problems associated with the control and estimation of financial systems governed by partial differential equations (e.g. the Black–Scholes partial differential equation (PDE) and its variants). Lastly it an offers optimal solution to the problem of statistical validation of computational models and tools used to support financial engineers in decision making. The application of state-space models in financial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for finance can be eliminated. It also allows methods of fault-free performance and optimality in the management of assets and capitals and methods assuring stability in the functioning of financial systems to be established. Covering the following key areas of financial engineering: (i) control and stabilization of financial systems dynamics, (ii) state estimation and forecasting, and (iii) statistical validation of decision-making tools, the book can be used for teaching undergraduate or postgraduate courses in financial engineering. It is also a useful resource for the engineering and computer science community
The present monograph offers a detailed and in-depth analysis of the topic of Intelligent Control for Electric Power Systems and Electric Vehicles. First, Nonlinear optimal control and Lie algebra-based control (Control based on approximate linearization and Global linearization-based control concepts) is analyzed. Next, Differential flatness theory and flatness-based control methods (Global linearization-based control with the use of differential flatness theory and Flatness-based control of nonlinear dynamical systems in cascading loops) is treated. Following the control theoretic part Control of DC and PMBLDC electric motors (Control of DC motors through a DC-DC converter and Control of Per- manent Magnet Brushless DC motors) is presented. Besides, Control of VSI-fed three-phase and multi- phase PMSMs (Nonlinear optimal control VSI-fed three-phase PMSMs and Nonlinear optimal control VSI-fed six-phase PMSMs) is explained. Additionally, Control of energy conversion chains based on PMSMs (Control of wind-turbine and PMSM-based electric power unit and Control of a PMSM-driven gas-compression unit) is studied. Besides, Control of energy conversion chains based on Induction Ma- chines (Control of the VSI-fed three-phase induction motor, Control of an induction motor-driven gas compressor and Control of induction generator-based shipboard microgrids) is explained. Next, Control of multi-phase machines in gas processing and power units (Control of gas-compressors actuated by 5-phase PMSMs and Control of 6-phase induction generators in renewable energy units) is introduced, Moreover, Control of Spherical Permanent Magnet Synchronous Motors and Switched Reluctance Mo- tors (Control of spherical permanent magnet synchronous motors, Control of switched reluctance motors for electric traction and Adaptive control for switched reluctance motors) is analyzed, Furthermore, Control of traction and powertrains in Electric Vehicles and Hybrid Electric Vehicles (Control of multi- phase motors in the traction system in electric vehicles and Control of synchronous machines and converters in power-chains of hybrid electric vehicles) is explained, Finally, Control of renewable power units and heat management units (Control of residential microgrids with Wind Generators, Fuel Cells and PVs and Control of heat pumps for thermal management in electric vehicles) it treated. The new control methods which are proposed by the monograph treat the control problem of the complex nonlinear dynamics of electric power systems and electric vehicles without the need for complicated state-space model transformations and changes of state variables. The proposed control schemes are modular and scalable and can be applied to a large class of dynamic models of electric power systems and electric vehicles. They have a clear and easy-to- implement algorithmic part, while they also exhibit a moderate computational load. The proposed control schemes foster the optimized exploitation of renewable energy sources and the reliable integration of renewable energy units in the power grid. Besides, they support the transition to electromotion and the deployment of the use of electric vehicles. The manuscript is suitable for teaching nonlinear control, estimation and fault diagnosis topics with emphasis to electric power systems and to electric vehicle traction and propulsion systems both at late undergraduate and postgraduate levels.
IEEE Technology and Engineering Management Society Body of Knowledge (TEMSBOK) IEEE TEMS Board of Directors-approved body of knowledge dedicated to technology and engineering management The IEEE Technology and Engineering Management Society Body of Knowledge (TEMSBOK) establishes a set of common practices for technology and engineering management, acts as a reference for entrepreneurs, establishes a basis for future official certifications, and summarizes the literature on the management field in order to publish reference documentation for new initiatives. The editors have used a template approach with authors that instructed them on how to introduce their manuscript, how to organize the technology and area fundamentals, the managing approach, techniques and benefits, realistic examples that show the application of concepts, recommended best use (focusing on how to identify the most adequate approach to typical cases), with a summary and conclusion of each section, plus a list of references for further study. The book is structured according to the following area knowledge chapters: business analysis, technology adoption, innovation, entrepreneurship, project management, digital disruption, digital transformation of industry, data science and management, and ethics and legal issues. Specific topics covered include: Market requirement analysis, business analysis for governance planning, financial analysis, evaluation and control, and risk analysis of market opportunities Leading and managing working groups, optimizing group creation and evolution, enterprise agile governance, and leading agile organizations and working groups Marketing plans for new products and services, risk analysis and challenges for entrepreneurs, and procurement and collaboration Projects, portfolios and programs, economic constraints and roles, integration management and control of change, and project plan structure The IEEE Technology and Engineering Management Society Body of Knowledge (TEMSBOK) will appeal to engineers, graduates, and professionals who wish to prepare for challenges in initiatives using new technologies, as well as managers who are responsible for conducting business involving technology and engineering.
This book reports on advanced theories and methods in three related fields of research: applied physics, system science and computers. It is organized in three parts, the first of which covers applied physics topics, including lasers and accelerators; condensed matter, soft matter and materials science; nanoscience and quantum engineering; atomic, molecular, optical and plasma physics; as well as nuclear and high-energy particle physics. It also addresses astrophysics, gravitation, earth and environmental science, as well as medical and biological physics. The second and third parts focus on advances in computers and system science, respectively, and report on automatic circuit control, power systems, computer communication, fluid mechanics, simulation and modeling, software engineering, data structures and applications of artificial intelligence among other areas. Offering a collection of contributions presented at the 2nd International Conference on Applied Physics, System Science and Computers (APSAC), held in Dubrovnik, Croatia on September 27–29, 2017, the book bridges the gap between applied physics and electrical engineering. It not only to presents new methods, but also promotes collaborations between different communities working on related topics at the interface between physics and engineering, with a special focus on communication, data modeling and visualization, quantum information, applied mechanics as well as bio and geophysics.
This volume discusses advances in applied nonlinear optimal control, comprising both theoretical analysis of the developed control methods and case studies about their use in robotics, mechatronics, electric power generation, power electronics, micro-electronics, biological systems, biomedical systems, financial systems and industrial production processes. The advantages of the nonlinear optimal control approaches which are developed here are that, by applying approximate linearization of the controlled systems’ state-space description, one can avoid the elaborated state variables transformations (diffeomorphisms) which are required by global linearization-based control methods. The book also applies the control input directly to the power unit of the controlled systems and not on an equivalent linearized description, thus avoiding the inverse transformations met in global linearization-based control methods and the potential appearance of singularity problems. The method adopted here also retains the known advantages of optimal control, that is, the best trade-off between accurate tracking of reference setpoints and moderate variations of the control inputs. The book’s findings on nonlinear optimal control are a substantial contribution to the areas of nonlinear control and complex dynamical systems, and will find use in several research and engineering disciplines and in practical applications.
This monograph addresses problems of: • nonlinear control, estimation and filtering for robotic manipulators (multi-degree-of freedom rigid-link robots, flexible-link robots, underactuated, redundant and cooperating manipulators and closed-chain robotic mechanisms); and• nonlinear control, estimation and filtering for autonomous robotic vehicles operating on the ground, in the air, and on and under water, independently and in cooperating groups. The book is a thorough treatment of the entire range of applications of robotic manipulators and autonomous vehicles. The nonlinear control and estimation methods it develops can be used generically, being suitable for a wide range of robotic systems. Such methods can improve robustness, precision and fault-tolerance in robotic manipulators and vehicles at the same time as enabling the reliable functioning of these systems under variable conditions, model uncertainty and external perturbations.
The present monograph offers a detailed and in-depth analysis of the topic of fault diagnosis for electric power systems and electric vehicles. First, the monograph treats the problem of Fault diagnosis with model-based and model-free techniques (Model-based fault diagnosis techniques and Model-free fault diagnosis techniques). Next, the monograph provides a solution for the problem of Control and fault diagnosis for Synchronous Generator-based renewable energy systems (Control of the marine-turbine and synchronous-generator unit and Fault diagnosis of the marine turbine and synchronous-generator unit. Additionally, the monograph introduces novel solutions for the problem of Fault diagnosis for electricity microgrids and gas processing units (Fault diagnosis for electric power DC microgrids and Fault diagnosis for electrically actuated gas compressors). Furthermore, the monograph analyzes and solves the problem of Fault diagnosis for gas and steam-turbine power generation units (Fault diagnosis for the gas-turbine and Synchronous Generator electric power unit and for the steam-turbine and synchronous generator power unit). Finally, the monograph provides a solution for the problem of Fault diagnosis for wind power units and for the distribution grid (Fault diagnosis for wind power generators and Fault diagnosis for the electric power distribution grid). The new fault detection and isolation methods that the monograph develops are of generic use and are addressed to a wide class of nonlinear dynamical systems, with emphasis on electric power systems and electric vehicles. On the one side, model-based fault detection and isolation methods are analyzed. In this case, known models about the dynamics of the monitored system are used by nonlinear state observers and Kalman Filters, which emulate the system’s fault-free condition. On the other side, model-free fault detection and isolation methods are analyzed. In this case, raw data are processed by neural networks and nonlinear regressors to generate models that emulate the fault-free condition of the monitored system. Statistical tests based on the processing of the residuals, which are formed between the outputs of the monitored system and the outputs of the fault-free model provide objective and almost infallible criteria about the occurrence of failures. The new fault detection and isolation methods with statistical procedures for defining fault thresholds enable early fault diagnosis and reveal incipient changes in the parameters of the monitored systems.
The remarkable growth of financial markets over the past decades has been accompanied by an equally remarkable explosion in financial engineering, the interdisciplinary field focusing on applications of mathematical and statistical modeling and computational technology to problems in the financial services industry. The goals of financial engineering research are to develop empirically realistic stochastic models describing dynamics of financial risk variables, such as asset prices, foreign exchange rates, and interest rates, and to develop analytical, computational and statistical methods and tools to implement the models and employ them to design and evaluate financial products and processes to manage risk and to meet financial goals. This handbook describes the latest developments in this rapidly evolving field in the areas of modeling and pricing financial derivatives, building models of interest rates and credit risk, pricing and hedging in incomplete markets, risk management, and portfolio optimization. Leading researchers in each of these areas provide their perspective on the state of the art in terms of analysis, computation, and practical relevance. The authors describe essential results to date, fundamental methods and tools, as well as new views of the existing literature, opportunities, and challenges for future research.
This comprehensive handbook discusses the most recent advances within the field of financial engineering, focusing not only on the description of the existing areas in financial engineering research, but also on the new methodologies that have been developed for modeling and addressing financial engineering problems. The book is intended for financial engineers, researchers, applied mathematicians, and graduate students interested in real-world applications to financial engineering.
This volume contains survey and research articles by some of the leading researchers in mathematical systems theory - a vibrant research area in its own right. Many authors have taken special care that their articles are self-contained and accessible also to non-specialists.