Petri nets are widely used in modeling, analysis, and control of discrete event systems arising from manufacturing, transportation, computer and communication networks, and web service systems. However, Petri net models for practical systems can be very large, making it difficult to apply such models to real-life problems. System Modeling and Control with Resource-Oriented Petri Nets introduces a new resource-oriented Petri net (ROPN) model that was developed by the authors. Not only does it successfully reduce model size, but it also offers improvements that facilitate effective modeling, analysis, and control of automated and reconfigurable manufacturing systems. Presenting the latest research in this novel approach, this cutting-edge volume provides proven theories and methodologies for implementing cost and time-saving improvements to contemporary manufacturing systems. It provides effective tools for deadlock avoidance-deadlock-free routing and deadlock-free scheduling. The authors supply simple and complex industrial manufacturing system examples to illustrate time-tested concepts, theories, and approaches for solving real-life application problems. Written in a clear and concise manner, the text covers applications to automated and reconfigurable manufacturing systems, automated guided vehicle (AGV) systems, semiconductor manufacturing systems, and flexible assembly systems. Explaining complex concepts in a manner that is easy to understand, the authors provide the understanding and tools needed for more effective modeling, analysis, performance evaluation, control, and scheduling of engineering processes that will lead to more flexible and efficient manufacturing systems.

Advances in mathematical methods, computer technology, and electrotechnical devices in particular continue to result in the creation of programs that are leading to increased labor productivity. Mathematical and simulation programs-and other programs that unite these two operations-provide the ability to calculate transitional, steady-state processes, stability conditions, and harmonic composition, and are often used to analyze processes in power electronic systems. Electrotechnical Systems: Calculation and Analysis with Mathematica and PSpice explores the potential of two such programs-Mathematica and ORCAD (PSpice)-as they are used for analysis in various areas. The authors discuss the formulation of problems and the steps in their solution. They focus on the analysis of transient, steady-state processes and their stability in non-stationary and nonlinear systems with DC and AC converters. All problems are solved using Mathematica, and program codes are presented. The authors use ORCAD (PSpice) to compare the results obtained by employing Mathematica and to demonstrate the peculiarities associated with its use. This book clearly and concisely illustrates represented expressions, variables, and functions and the general application of the mathematical pocket Mathematica 4.2 for the analysis of the electromagnetic processes in electrotechnical systems. It will be a valuable addition to the library of anyone working with electrotechnical systems.

The demands of increasingly complex embedded systems and associated performance computations have resulted in the development of heterogeneous computing architectures that often integrate several types of processors, analog and digital electronic components, and mechanical and optical components-all on a single chip. As a result, now the most prominent challenge for the design automation community is to efficiently plan for such heterogeneity and to fully exploit its capabilities. A compilation of work from internationally renowned authors, Model-Based Design for Embedded Systems elaborates on related practices and addresses the main facets of heterogeneous model-based design for embedded systems, including the current state of the art, important challenges, and the latest trends. Focusing on computational models as the core design artifact, this book presents the cutting-edge results that have helped establish model-based design and continue to expand its parameters. The book is organized into three sections: Real-Time and Performance Analysis in Heterogeneous Embedded Systems, Design Tools and Methodology for Multiprocessor System-on-Chip, and Design Tools and Methodology for Multidomain Embedded Systems. The respective contributors share their considerable expertise on the automation of design refinement and how to relate properties throughout this refinement while enabling analytic and synthetic qualities. They focus on multi-core methodological issues, real-time analysis, and modeling and validation, taking into account how optical, electronic, and mechanical components often interface. Model-based design is emerging as a solution to bridge the gap between the availability of computational capabilities and our inability to make full use of them yet. This approach enables teams to start the design process using a high-level model that is gradually refined through abstraction levels to ultimately yield a prototype. When executed well, model-based design encourages enhanced performance and quicker time to market for a product. Illustrating a broad and diverse spectrum of applications such as in the automotive aerospace, health care, consumer electronics, this volume provides designers with practical, readily adaptable modeling solutions for their own practice.

Carefully separating the essential from the ornamental, Essentials of Control Techniques and Theory presents the nuts and bolts for designing a successful controller. It discusses the theory required to support the art of designing a working controller as well as the various aspects to convince a client, employer, or examiner of your expertise. A Compelling Account of the Basics of Control Theory Control solutions for practicing engineers Using the author's own Javascript On-Line Learning Interactive Environment for Simulation (Jollies), the text relies on computer-based graphical analysis methods, such as Nyquist, Nichols, root locus, and phase-plane, to illustrate how useful computer simulation can be for analyzing both linear and nonlinear systems. It explains step-by-step the design and modeling of various control systems, including discrete time systems and an inverted pendulum. Along with offering many web-based simulations, the book shows how mathematics, such as vectors, matrices, and the differential equations that govern state variables, can help us understand the concepts that underpin the controller's effects. From frequency domain analysis to time-domain state-space representation, this book covers many aspects of classical and modern control theory. It presents important methods for designing and analyzing linear systems and controllers.

Designed for undergraduate students in the general science, engineering, and mathematics community, Introduction to the Simulation of Dynamics Using Simulink (R) shows how to use the powerful tool of Simulink to investigate and form intuitions about the behavior of dynamical systems. Requiring no prior programming experience, it clearly explains how to transition from physical models described by mathematical equations directly to executable Simulink simulations. Teaches students how to model and explore the dynamics of systemsStep by step, the author presents the basics of building a simulation in Simulink. He begins with finite difference equations and simple discrete models, such as annual population models, to introduce the concept of state. The text then covers ordinary differential equations, numerical integration algorithms, and time-step simulation. The final chapter offers overviews of some advanced topics, including the simulation of chaotic dynamics and partial differential equations. A one-semester undergraduate course on simulationWritten in an informal, accessible style, this guide includes many diagrams and graphics as well as exercises embedded within the text. It also draws on numerous examples from the science, engineering, and technology fields. The book deepens students' understanding of simulated systems and prepares them for advanced and specialized studies in simulation. Ancillary materials are available at http://nw08.american.edu/~gray

Modeling and Control in Vibrational and Structural Dynamics: A Differential Geometric Approach describes the control behavior of mechanical objects, such as wave equations, plates, and shells. It shows how the differential geometric approach is used when the coefficients of partial differential equations (PDEs) are variable in space (waves/plates), when the PDEs themselves are defined on curved surfaces (shells), and when the systems have quasilinear principal parts. To make the book self-contained, the author starts with the necessary background on Riemannian geometry. He then describes differential geometric energy methods that are generalizations of the classical energy methods of the 1980s. He illustrates how a basic computational technique can enable multiplier schemes for controls and provide mathematical models for shells in the form of free coordinates. The author also examines the quasilinearity of models for nonlinear materials, the dependence of controllability/stabilization on variable coefficients and equilibria, and the use of curvature theory to check assumptions. With numerous examples and exercises throughout, this book presents a complete and up-to-date account of many important advances in the modeling and control of vibrational and structural dynamics.

Micro/nano-scale engineering-especially the design and implementation of ultra-fast and ultra-scale energy devices, sensors, and cellular and molecular systems-remains a daunting challenge. Modeling and control has played an essential role in many technological breakthroughs throughout the course of history. Therefore, the need for a practical guide to modeling and control for micro/nano-scale devices and systems has emerged. The first edited volume to address this rapidly growing field, Modeling and Control for Micro/Nano Devices and Systems gives control engineers, lab managers, high-tech researchers, and graduate students easy access to the expert contributors' cutting-edge knowledge of micro/nanotechnology, energy, and bio-systems. The editors offer an integrated view from theory to practice, covering diverse topics ranging from micro/nano-scale sensors to energy devices and control of biology systems in cellular and molecular levels. The book also features numerous case studies for modeling of micro/nano devices and systems, and explains how the models can be used for control and optimization purposes. Readers benefit from learning the latest modeling techniques for micro/nano-scale devices and systems, and then applying those techniques to their own research and development efforts.

Mechatronic systems are used in a range of consumer products from large-scale braking systems in vehicular agents to small-scale integrated sensors in mobile phones. To keep pace in the competitive consumer electronics industry, companies need to continuously improve servo evaluation and position control of these mechatronic systems. Advances in High-Performance Motion Control of Mechatronic Systems covers advanced control topics for mechatronic applications. In particular, the book examines control systems design for ultra-fast and ultra-precise positioning of mechanical actuators in mechatronic systems. The book systematically describes motion control design methods for trajectory design, sampled-data precise positioning, transient control using switching control, and dual-stage actuator control. Each method is described in detail, from theoretical aspects to examples of actual industry applications including hard disk drives, optical disk drives, galvano scanners, personal mobility robots, and more. This helps readers better understand how to translate control theories and algorithms from theory to design and implementation in realistic engineering systems. The book also identifies important research directions and advanced control techniques that may provide solutions for the next generation of high-performance mechatronics. Bridging research and industry, this book presents state-of-the-art control design methodologies that are widely applicable to industries such as manufacturing, robotics, home appliances, automobiles, printers, and optical drives. It guides readers toward more effective solutions for high-performance mechatronic systems in their own products.

Computer-Aided Control Systems Design: Practical Applications Using MATLAB (R) and Simulink (R) supplies a solid foundation in applied control to help you bridge the gap between control theory and its real-world applications. Working from basic principles, the book delves into control systems design through the practical examples of the ALSTOM gasifier system in power stations and underwater robotic vehicles in the marine industry. It also shows how powerful software such as MATLAB (R) and Simulink (R) can aid in control systems design. Make Control Engineering Come Alive with Computer-Aided Software Emphasizing key aspects of the design process, the book covers the dynamic modeling, control structure design, controller design, implementation, and testing of control systems. It begins with the essential ideas of applied control engineering and a hands-on introduction to MATLAB and Simulink. It then discusses the analysis, model order reduction, and controller design for a power plant and the modeling, simulation, and control of a remotely operated vehicle (ROV) for pipeline tracking. The author explains how to obtain the ROV model and verify it by using computational fluid dynamic software before designing and implementing the control system. In addition, the book details the nonlinear subsystem modeling and linearization of the ROV at vertical plane equilibrium points. Throughout, the author delineates areas for further study. Appendices provide additional information on various simulation models and their results. Learn How to Perform Simulations on Real Industry Systems A step-by-step guide to computer-aided applied control design, this book supplies the knowledge to help you deal with control problems in industry. It is a valuable reference for anyone who wants a better understanding of the theory and practice of basic control systems design, analysis, and implementation.

Distributed controller design is generally a challenging task, especially for multi-agent systems with complex dynamics, due to the interconnected effect of the agent dynamics, the interaction graph among agents, and the cooperative control laws. Cooperative Control of Multi-Agent Systems: A Consensus Region Approach offers a systematic framework for designing distributed controllers for multi-agent systems with general linear agent dynamics, linear agent dynamics with uncertainties, and Lipschitz nonlinear agent dynamics. Beginning with an introduction to cooperative control and graph theory, this monograph: Explores the consensus control problem for continuous-time and discrete-time linear multi-agent systems Studies the H and H2 consensus problems for linear multi-agent systems subject to external disturbances Designs distributed adaptive consensus protocols for continuous-time linear multi-agent systems Considers the distributed tracking control problem for linear multi-agent systems with a leader of nonzero control input Examines the distributed containment control problem for the case with multiple leaders Covers the robust cooperative control problem for multi-agent systems with linear nominal agent dynamics subject to heterogeneous matching uncertainties Discusses the global consensus problem for Lipschitz nonlinear multi-agent systems Cooperative Control of Multi-Agent Systems: A Consensus Region Approach provides a novel approach to designing distributed cooperative protocols for multi-agent systems with complex dynamics. The proposed consensus region decouples the design of the feedback gain matrices of the cooperative protocols from the communication graph and serves as a measure for the robustness of the protocols to variations of the communication graph. By exploiting the decoupling feature, adaptive cooperative protocols are presented that can be designed and implemented in a fully distributed fashion.

Mobile manipulators combine the advantages of mobile platforms and robotic arms, extending their operational range and functionality to large spaces and remote, demanding, and/or dangerous environments. They also bring complexity and difficulty in dynamic modeling and control system design. However, advances in nonlinear system analysis and control system design offer powerful tools and concepts for the control of mobile manipulator systems. Fundamentals in Modeling and Control of Mobile Manipulators presents a thorough theoretical treatment of several fundamental problems for mobile robotic manipulators. The book integrates fresh concepts and state-of-the-art results to systematically examine kinematics and dynamics, motion generation, feedback control, coordination, and cooperation. From this treatment, the authors form a basic theoretical framework for a mobile robotic manipulator that extends the theory of nonlinear control and applies to more realistic problems. Drawing on their research over the past ten years, the authors propose novel control theory concepts and techniques to tackle key problems. Topics covered include kinematic and dynamic modeling, control of nonholonomic systems, path planning that considers motion and manipulation, hybrid motion/force control and hybrid position/force control where the mobile manipulator is required to interact with environments, and coordination and cooperation strategies for multiple mobile manipulators. The book also includes practical examples of applications in engineering systems. This timely book investigates important scientific and engineering issues for researchers and engineers working with either single or multiple mobile manipulators for larger operational space, better cooperation, and improved productivity.

Optimal Control for Chemical Engineers gives a detailed treatment of optimal control theory that enables readers to formulate and solve optimal control problems. With a strong emphasis on problem solving, the book provides all the necessary mathematical analyses and derivations of important results, including multiplier theorems and Pontryagin's principle. The text begins by introducing various examples of optimal control, such as batch distillation and chemotherapy, and the basic concepts of optimal control, including functionals and differentials. It then analyzes the notion of optimality, describes the ubiquitous Lagrange multipliers, and presents the celebrated Pontryagin principle of optimal control. Building on this foundation, the author examines different types of optimal control problems as well as the required conditions for optimality. He also describes important numerical methods and computational algorithms for solving a wide range of optimal control problems, including periodic processes. Through its lucid development of optimal control theory and computational algorithms, this self-contained book shows readers how to solve a variety of optimal control problems.

Principles of Power Engineering Analysis presents the basic tools required to understand the components in an electric power transmission system. Classroom-tested at Rensselaer Polytechnic Institute, this text is the only up-to-date one available that covers power system analysis at the graduate level. The book explains from first principles the expressions that predict the performance of transmission systems and transformers. It then extends these concepts to balanced three-phase systems and unbalanced systems. The authors proceed to introduce symmetrical component analysis of transmission systems, three-phase transformers, and faulted systems. They also describe the design of untransposed transmission lines and discuss other analysis component systems, such as Clarke component networks. Despite the tremendous changes that have occurred in the electrical industry over the last forty years, the need for a fundamental understanding of power system analysis has not changed. Suitable for a one-semester course, this book develops the necessary concepts in depth and illustrates the application of three-phase electric power transmission.

Long span suspension bridges cost billions. In recent decades, structural health monitoring systems have been developed to measure the loading environment and responses of these bridges in order to assess serviceability and safety while tracking the symptoms of operational incidents and potential damage. This helps ensure the bridge functions properly during a long service life and guards against catastrophic failure under extreme events. Although these systems have achieved some success, this cutting-edge technology involves many complex topics that present challenges to students, researchers, and engineers alike. Systematically introducing the fundamentals and outlining the advanced technologies for achieving effective long-term monitoring, Structural Health Monitoring of Long-Span Suspension Bridges covers: The design of structural health monitoring systems Finite element modelling and system identification Highway loading monitoring and effects Railway loading monitoring and effects Temperature monitoring and thermal behaviour Wind monitoring and effects Seismic monitoring and effects SHMS-based rating method for long span bridge inspection and maintenance Structural damage detection and test-bed establishment These are applied in a rigorous case study, using more than ten years' worth of data, to the Tsing Ma suspension bridge in Hong Kong to examine their effectiveness in the operational performance of a real bridge. The Tsing Ma bridge is the world's longest suspension bridge to carry both a highway and railway, and is located in one of the world's most active typhoon regions. Bridging the gap between theory and practice, this is an ideal reference book for students, researchers, and engineering practitioners.

Magnetorheological Fluid Technology: Applications in Vehicle Systems compiles the authors' recent work involving the application of magnetorheological (MR) fluids and other smart materials in vehicles. It collects concepts that have previously been scattered in peer-reviewed international journals. After introducing the physical phenomena and properties of MR fluids, the book presents control methodologies for effectively controlling vehicle devices and systems featuring MR fluids. The authors also introduce the hysteresis identification of MR fluid and discuss its application through the adoption of the Preisach and polynomial models. They then describe the application of MR-equipped suspension systems in passenger, tracked, and railway vehicles; the application of MR brake systems in passenger vehicles, motorcycles, and bicycles; and the application of several MR technologies in heavy vehicles. The final chapter explores the use of haptic technologies for easily operating vehicle instruments and achieving optimal gear shifting with accelerator pedals. Assuming some technical and mathematical background in vibration, dynamics, and control, this book is designed for scientists and engineers looking to create new devices or systems for vehicles featuring controllable MR fluids. It is also suitable for graduate students who are interested in the dynamic modeling and control methodology of vehicle devices and systems associated with MR fluid technology.

Significant progress has been made on nonlinear control systems in the past two decades. However, many of the existing nonlinear control methods cannot be readily used to cope with communication and networking issues without nontrivial modifications. For example, small quantization errors may cause the performance of a "well-designed" nonlinear control system to deteriorate. Motivated by the need for new tools to solve complex problems resulting from smart power grids, biological processes, distributed computing networks, transportation networks, robotic systems, and other cutting-edge control applications, Nonlinear Control of Dynamic Networks tackles newly arising theoretical and real-world challenges for stability analysis and control design, including nonlinearity, dimensionality, uncertainty, and information constraints as well as behaviors stemming from quantization, data-sampling, and impulses. Delivering a systematic review of the nonlinear small-gain theorems, the text: Supplies novel cyclic-small-gain theorems for large-scale nonlinear dynamic networks Offers a cyclic-small-gain framework for nonlinear control with static or dynamic quantization Contains a combination of cyclic-small-gain and set-valued map designs for robust control of nonlinear uncertain systems subject to sensor noise Presents a cyclic-small-gain result in directed graphs and distributed control of nonlinear multi-agent systems with fixed or dynamically changing topology Based on the authors' recent research, Nonlinear Control of Dynamic Networks provides a unified framework for robust, quantized, and distributed control under information constraints. Suggesting avenues for further exploration, the book encourages readers to take into consideration more communication and networking issues in control designs to better handle the arising challenges.

Tensor Product Model Transformation in Polytopic Model-Based Control offers a new perspective of control system design. Instead of relying solely on the formulation of more effective LMIs, which is the widely adopted approach in existing LMI-related studies, this cutting-edge book calls for a systematic modification and reshaping of the polytopic convex hull to achieve enhanced performance. Varying the convexity of the resulting TP canonical form is a key new feature of the approach. The book concentrates on reducing analytical derivations in the design process, echoing the recent paradigm shift on the acceptance of numerical solution as a valid form of output to control system problems. The salient features of the book include: Presents a new HOSVD-based canonical representation for (qLPV) models that enables trade-offs between approximation accuracy and computation complexity Supports a conceptually new control design methodology by proposing TP model transformation that offers a straightforward way of manipulating different types of convexity to appear in polytopic representation Introduces a numerical transformation that has the advantage of readily accommodating models described by non-conventional modeling and identification approaches, such as neural networks and fuzzy rules Presents a number of practical examples to demonstrate the application of the approach to generate control system design for complex (qLPV) systems and multiple control objectives. The authors' approach is based on an extended version of singular value decomposition applicable to hyperdimensional tensors. Under the approach, trade-offs between approximation accuracy and computation complexity can be performed through the singular values to be retained in the process. The use of LMIs enables the incorporation of multiple performance objectives into the control design problem and assurance of a solution via convex optimization if feasible. Tensor Product Model Transformation in Polytopic Model-Based Control includes examples and incorporates MATLAB (R) Toolbox TPtool. It provides a reference guide for graduate students, researchers, engineers, and practitioners who are dealing with nonlinear systems control applications.

Edited by Takashi Yamaguchi, Mitsuo Hirate, and Chee Khiang Pang, with contributions from pioneers known for their ground-breaking work, High-Speed Precision Motion Control discusses high-precision and fast servo controls in hard disk drives (HDDs). The chapter authors describe the control technologies they've developed, most of which have already been successfully applied to mass production of HDDs. As the proposed methodologies have been verified on commercial HDDs at the very least, these advanced control technologies can also be readily applied to precision motion control of other mechatronic systems, e.g., scanners, micro-positioners, photocopiers, atomic force microscopes (AFMs), etc. Each self-contained chapter progresses from concept to technique and presents application examples in automotive, aerospace, aeronautical, and manufacturing engineering. The control technologies are categorized into high-speed servo control, precision control, and environment-friendly control, making it easy to find an appropriate control technology according to their domain of application. The book also makes MATLAB (R)/SIMULINK (R) codes for benchmark problems available for download. The control technologies described range from fundamental classical control theories to advanced topics such as multi-rate control. The content contains a healthy balance between materials from the contributor's research works and that in the wider literature. The resulting resource empowers engineers and managers with the knowledge and know-how to make important decisions and policies.

Modern semiconductor devices have reached high current and voltage levels, and their power-handling limits can be extended if they are used in multilevel converter configurations. To create high-performance and reliable control designs, however, engineers need in-depth understanding of the characteristics and operation of these topologies. Multilevel Converters for Industrial Applications presents a thorough and comprehensive analysis of multilevel converters with a common DC voltage source. The book offers a novel perspective to help readers understand the principles of the operation of voltage-source multilevel converters as power processors, and their capabilities and limitations. The book begins with an overview of medium-voltage power converters and their applications. It then analyzes the topological characteristics of the diode-clamped multilevel converter, the flying capacitor multilevel converter, and the asymmetric cascaded multilevel converter. For each topology, the authors highlight particular control issues and design trade-offs. They also develop relevant modulation and control strategies. Numerous graphical representations aid in the analysis of the topologies and are useful for beginning the analysis of new multilevel converter topologies. The last two chapters of the book explore two case studies that analyze the behavior of the cascade asymmetric multilevel converter as a distribution static compensator and shunt active power filter, and the behavior of the diode-clamped topology configured as a back-to-back converter. These case studies demonstrate how to address the associated control problems with advanced control and modulation schemes. Examining recent advances, this book provides deep insight on the design of high-power multilevel converters and their applications. It is a valuable reference for anyone interested in medium-voltage power conversion, which is increasingly being used in industry and in renewable energy and distributed generation systems to improve efficiency and operation flexibility.

While global demand for photovoltaic (PV) modules has increased approximately 45 percent per year over the past decade, PV modules must be durable and inexpensive to compete with traditional energy resources. Often overlooked as a means to improve solar technology, polymer packaging is not only the key to protecting fragile solar cells from environmental factors, but is also the critical path for increasing the power performance of a PV module Solar Module Packaging: Polymeric Requirements and Selection explores current and future opportunities in PV polymeric packaging, emphasizing how it can simultaneously reduce cost, increase weatherability, and improve a PV module's power. The book offers an insider's perspective on the manufacturing processes and needs of the solar industry and reveals opportunities for future material development and processing. A broad survey of the polymeric packaging of solar cells, the text covers various classifications of polymers, their material properties, and optimal processing conditions. Taking a practical approach to material selection, it emphasizes industrial requirements for material development, such as cost reduction, increased material durability, improved module performance, and ease of processing. Addressing cost and profitability, the author examines the economics behind polymeric packaging and how it influences the selection process used by solar companies. Suitable for nonspecialists in polymer science, the book provides a basic understanding of polymeric concepts, fundamental properties, and processing techniques commonly used in solar module packaging. It presents guidelines for using polymers in commercial PV modules as well as the tests required to establish confidence in the selection process.

The main focus of this monograph will be on the Enhanced Anti-Disturbance Control and filtering theory and their applications. In fact, the classical anti-disturbance control theory only considered one "equivalent" disturbance which is merged by different unknown sources. However, it is noted that along with the development of information obtaining and processing technologies, one can get more information or knowledge about various types of disturbances.

Measurement Data Modeling and Parameter Estimation integrates mathematical theory with engineering practice in the field of measurement data processing. Presenting the first-hand insights and experiences of the authors and their research group, it summarizes cutting-edge research to facilitate the application of mathematical theory in measurement and control engineering, particularly for those interested in aeronautics, astronautics, instrumentation, and economics. Requiring a basic knowledge of linear algebra, computing, and probability and statistics, the book illustrates key lessons with tables, examples, and exercises. It emphasizes the mathematical processing methods of measurement data and avoids the derivation procedures of specific formulas to help readers grasp key points quickly and easily. Employing the theories and methods of parameter estimation as the fundamental analysis tool, this reference: Introduces the basic concepts of measurements and errors Applies ideas from mathematical branches, such as numerical analysis and statistics, to the modeling and processing of measurement data Examines methods of regression analysis that are closely related to the mathematical processing of dynamic measurement data Covers Kalman filtering with colored noises and its applications Converting time series models into problems of parameter estimation, the authors discuss modeling methods for the true signals to be estimated as well as systematic errors. They provide comprehensive coverage that includes model establishment, parameter estimation, abnormal data detection, hypothesis tests, systematic errors, trajectory parameters, and modeling of radar measurement data. Although the book is based on the authors' research and teaching experience in aeronautics and astronautics data processing, the theories and methods introduced are applicable to processing dynamic measurement data across a wide range of fields.

Using real-life examples to illustrate the performance of learning algorithms and instructing readers how to apply them to practical applications, this work offers a comprehensive treatment of subspace learning algorithms for neural networks. The authors summarize a decade of high quality research offering a host of practical applications. They demonstrate ways to extend the use of algorithms to fields such as encryption communication, data mining, computer vision, and signal and image processing to name just a few. The brilliance of the work lies with how it coherently builds a theoretical understanding of the convergence behavior of subspace learning algorithms through a summary of chaotic behaviors.

This book presents an overview of the risks involved in modern electricity production, delivery and trading, including technical risk in production, transportation and delivery, operational risk for the system operators, market risks for traders, and political and other long term risks in strategic management.Using decision making under uncertainty as a methodological background, the book is divided into four parts, with Part I focusing on energy markets, particularly electricity markets.Topics include a nontechnical overview of energy markets and their main properties, basic price models for energy commodity prices, and modeling approaches for electricity price processes.

Part II looks at optimal decisions in managing energy systems, including hydropower dispatch models, cutting plane algorithms and approximative dynamic programming; hydro-thermal production; renewable; stochastic investments and operational optimization models for natural gas transport; decision making in operating electricity networks; and investment in extending energy production systems.

Part III explores pricing, including electricity swing options and the pricing of derivatives with volume control. Part IV looks at long-term and political risks, including energy systems under aspects of climate change, and catastrophic operational risks, particularly risks from terrorist attacks."

In an era of intense competition where plant operating efficiencies must be maximized, downtime due to machinery failure has become more costly. To cut operating costs and increase revenues, industries have an urgent need to predict fault progression and remaining lifespan of industrial machines, processes, and systems. An engineer who mounts an acoustic sensor onto a spindle motor wants to know when the ball bearings will wear out without having to halt the ongoing milling processes. A scientist working on sensor networks wants to know which sensors are redundant and can be pruned off to save operational and computational overheads. These scenarios illustrate a need for new and unified perspectives in system analysis and design for engineering applications. Intelligent Diagnosis and Prognosis of Industrial Networked Systems proposes linear mathematical tool sets that can be applied to realistic engineering systems. The book offers an overview of the fundamentals of vectors, matrices, and linear systems theory required for intelligent diagnosis and prognosis of industrial networked systems. Building on this theory, it then develops automated mathematical machineries and formal decision software tools for real-world applications. The book includes portable tool sets for many industrial applications, including: Forecasting machine tool wear in industrial cutting machines Reduction of sensors and features for industrial fault detection and isolation (FDI) Identification of critical resonant modes in mechatronic systems for system design of R&D Probabilistic small-signal stability in large-scale interconnected power systems Discrete event command and control for military applications The book also proposes future directions for intelligent diagnosis and prognosis in energy-efficient manufacturing, life cycle assessment, and systems of systems architecture. Written in a concise and accessible style, it presents tools that are mathematically rigorous but not involved. Bridging academia, research, and industry, this reference supplies the know-how for engineers and managers making decisions about equipment maintenance, as well as researchers and students in the field.