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Introduction to Nonlinear Control : Stability, Control Design, and Estimation
An introductory text on the analysis, control, and estimation of nonlinear systems, appropriate for advanced undergraduate and graduate studentsThis self-contained and accessible introduction to the concepts and techniques used for nonlinear feedback systems offers a holistic treatment suitable for use in both advanced undergraduate and graduate courses; students need only some familiarity with differential equations and linear algebra to understand the material presented.The text begins with an overview of stability and Lyapunov methods for nonlinear systems, with Lyapunov’s second method revisited throughout the book as a connective thread.Other introductory chapters cover linear systems, frequency domain methods, and discrete-time systems.Building on this background material, the book provides a broad introduction to the basic ideas underpinning major themes of research in nonlinear control, including input-to-state stability, sliding mode control, adaptive control, feedback linearization, and robust output regulation.Chapters also cover observer design and estimation for nonlinear systems.The text is notable for its coverage of nonlinear model predictive control and its introduction to the use of linear matrix inequalities and semidefinite programming coupled with their use in modern antiwindup designs. • First text on nonlinear control appropriate for undergraduates• Suitable both for students preparing for rigorous graduate study and for those entering technical fields outside of academia• Unique in its coverage of recent research topics• Pedagogical features including extensive chapter summaries, examples, and appendixes with definitions, results, and MATLAB applications
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Bayesian Estimation of DSGE Models
Dynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks.This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models.The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood function.The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided.The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations. Bayesian Estimation of DSGE Models is essential reading for graduate students, academic researchers, and practitioners at policy institutions.
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Filter Design for System Modeling, State Estimation and Fault Diagnosis
Filter Design for System Modeling, State Estimation and Fault Diagnosis analyzes the latest methods in the design of filters for system modeling, state estimation and fault detection with the intention of providing a new perspective of both theoretical and practical aspects. This book also includes fault diagnosis techniques for unknown but bounded systems, their real applications on modeling and fault diagnosis for lithium battery systems, DC-DC converters and spring damping systems.It proposes new methods based on zonotopic Kalman filtering, a variety of state estimation methods of zonotope and its derived algorithms, a state estimation method based on convex space, set inversion interval observer filtering-based guaranteed fault estimation and a novel interval observer filtering-based fault diagnosis.The methods presented in this text are more practical than the common probabilistic-based algorithms, since these can be applied in unknown but bounded noisy environments.This book will be an essential read for students, scholars and engineering professionals who are interested in filter design, system modeling, state estimation, fault diagnosis and related fields.
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Cyber-Physical Power Systems State Estimation
Cyber-Physical Power System State Estimation updates classic state estimation tools to enable real-time operations and optimize reliability in modern electric power systems.The work introduces and contextualizes the core concepts and classic approaches to state estimation modeling.It builds on these classic approaches with a suite of data-driven models and non-synchronized measurement tools to reflect current measurement trends required by increasingly more sophisticated grids.Chapters outline core definitions, concepts and the network analysis procedures involved in the real-time operation of EPS. Specific sections introduce power flow problem in EPS, highlighting network component modeling and power flow equations for state estimation before addressing quasi static state estimation in electrical power systems using Weighted Least Squares (WLS) classical and alternatives formulations.Particularities of the state estimation process in distribution systems are also considered.Finally, the work goes on to address observability analysis, measurement redundancy and the processing of gross errors through the analysis of WLS static state estimator residuals.
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Estimation of the Time Since Death
Estimation of the Time Since Death remains the foremost authoritative book on scientifically calculating the estimated time of death postmortem.Building on the success of previous editions which covered both the early and later postmortem periods this edition includes a new chapter on DNA/RNA degradation and further new content on drug testing in hair, thus widening the scope of the material.Chapters have been improved, updated and expanded, and include new and additional images to enhance the text.A unique work of synthesis combining rigorous science with practical guidance, this update reinforces the book’s reputation as an invaluable resource – and also the standard – for the estimation of the time since death.
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Software Estimation : Demystifying the Black Art
Often referred to as the “black art” because of its complexity and uncertainty, software estimation is not as difficult or puzzling as people think.In fact, generating accurate estimates is straightforward—once you understand the art of creating them.In his highly anticipated book, acclaimed author Steve McConnell unravels the mystery to successful software estimation—distilling academic information and real-world experience into a practical guide for working software professionals.Instead of arcane treatises and rigid modeling techniques, this guide highlights a proven set of procedures, understandable formulas, and heuristics that individuals and development teams can apply to their projects to help achieve estimation proficiency. Discover how to: Estimate schedule and cost—or estimate the functionality that can be delivered within a given time frame Avoid common software estimation mistakes Learn estimation techniques for you, your team, and your organization * Estimate specific project activities—including development, management, and defect correction Apply estimation approaches to any type of project—small or large, agile or traditional Navigate the shark-infested political waters that surround project estimates When many corporate software projects are failing, McConnell shows you what works for successful software estimation.
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Reserves Estimation for Geopressured Gas Reservoirs
Reserves Estimation for Geopressured Gas Reservoirs aims to introduce the principles and methods for calculating reserves of geopressured gas reservoirs with the material balance method, presenting advantages, disadvantages and applicable conditions of various methods.The book, based on manual analysis, explains methods and calculation steps with more than 30 gas reservoir examples.It will help gas reservoir engineers learn basic principles and calculation methods and familiarize themselves with the content of the software Black Box, which in turn helps improve the level of gas field performance analysis and the level of gas field development.
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Small Area Estimation and Microsimulation Modeling
Small Area Estimation and Microsimulation Modeling is the first practical handbook that comprehensively presents modern statistical SAE methods in the framework of ultramodern spatial microsimulation modeling while providing the novel approach of creating synthetic spatial microdata.Along with describing the necessary theories and their advantages and limitations, the authors illustrate the practical application of the techniques to a large number of substantive problems, including how to build up models, organize and link data, create synthetic microdata, conduct analyses, yield informative tables and graphs, and evaluate how the findings effectively support the decision making processes in government and non-government organizations. FeaturesCovers both theoretical and applied aspects for real-world comparative research and regional statistics productionThoroughly explains how microsimulation modeling technology can be constructed using available datasets for reliable small area statisticsProvides SAS codes that allow readers to utilize these latest technologies in their own work. This book is designed for advanced graduate students, academics, professionals and applied practitioners who are generally interested in small area estimation and/or microsimulation modeling and dealing with vital issues in social and behavioural sciences, applied economics and policy analysis, government and/or social statistics, health sciences, business, psychology, environmental and agriculture modeling, computational statistics and data simulation, spatial statistics, transport and urban planning, and geospatial modeling.
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