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The State Space Method
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Book Synopsis State-Space Methods for Time Series Analysis by : Jose Casals
Download or read book State-Space Methods for Time Series Analysis written by Jose Casals and published by CRC Press. This book was released on 2018-09-03 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: The state-space approach provides a formal framework where any result or procedure developed for a basic model can be seamlessly applied to a standard formulation written in state-space form. Moreover, it can accommodate with a reasonable effort nonstandard situations, such as observation errors, aggregation constraints, or missing in-sample values. Exploring the advantages of this approach, State-Space Methods for Time Series Analysis: Theory, Applications and Software presents many computational procedures that can be applied to a previously specified linear model in state-space form. After discussing the formulation of the state-space model, the book illustrates the flexibility of the state-space representation and covers the main state estimation algorithms: filtering and smoothing. It then shows how to compute the Gaussian likelihood for unknown coefficients in the state-space matrices of a given model before introducing subspace methods and their application. It also discusses signal extraction, describes two algorithms to obtain the VARMAX matrices corresponding to any linear state-space model, and addresses several issues relating to the aggregation and disaggregation of time series. The book concludes with a cross-sectional extension to the classical state-space formulation in order to accommodate longitudinal or panel data. Missing data is a common occurrence here, and the book explains imputation procedures necessary to treat missingness in both exogenous and endogenous variables. Web Resource The authors’ E4 MATLAB® toolbox offers all the computational procedures, administrative and analytical functions, and related materials for time series analysis. This flexible, powerful, and free software tool enables readers to replicate the practical examples in the text and apply the procedures to their own work.
Book Synopsis Control System Design by : Bernard Friedland
Download or read book Control System Design written by Bernard Friedland and published by Courier Corporation. This book was released on 2012-03-08 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to state-space methods covers feedback control; state-space representation of dynamic systems and dynamics of linear systems; frequency-domain analysis; controllability and observability; shaping the dynamic response; more. 1986 edition.
Book Synopsis Linear State-Space Control Systems by : Robert L. Williams, II
Download or read book Linear State-Space Control Systems written by Robert L. Williams, II and published by John Wiley & Sons. This book was released on 2007-02-09 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book blends readability and accessibility common to undergraduate control systems texts with the mathematical rigor necessary to form a solid theoretical foundation. Appendices cover linear algebra and provide a Matlab overivew and files. The reviewers pointed out that this is an ambitious project but one that will pay off because of the lack of good up-to-date textbooks in the area.
Book Synopsis Linear System Theory by : Frank M. Callier
Download or read book Linear System Theory written by Frank M. Callier and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the result of our teaching over the years an undergraduate course on Linear Optimal Systems to applied mathematicians and a first-year graduate course on Linear Systems to engineers. The contents of the book bear the strong influence of the great advances in the field and of its enormous literature. However, we made no attempt to have a complete coverage. Our motivation was to write a book on linear systems that covers finite dimensional linear systems, always keeping in mind the main purpose of engineering and applied science, which is to analyze, design, and improve the performance of phy sical systems. Hence we discuss the effect of small nonlinearities, and of perturbations of feedback. It is our on the data; we face robustness issues and discuss the properties hope that the book will be a useful reference for a first-year graduate student. We assume that a typical reader with an engineering background will have gone through the conventional undergraduate single-input single-output linear systems course; an elementary course in control is not indispensable but may be useful for motivation. For readers from a mathematical curriculum we require only familiarity with techniques of linear algebra and of ordinary differential equations.
Book Synopsis Time Series Analysis by State Space Methods by : James Durbin
Download or read book Time Series Analysis by State Space Methods written by James Durbin and published by OUP Oxford. This book was released on 2012-05-03 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. Additions to this second edition include the filtering of nonlinear and non-Gaussian series. Part I of the book obtains the mean and variance of the state, of a variable intended to measure the effect of an interaction and of regression coefficients, in terms of the observations. Part II extends the treatment to nonlinear and non-normal models. For these, analytical solutions are not available so methods are based on simulation.
Book Synopsis The State Space Method by : Daniel Alpay
Download or read book The State Space Method written by Daniel Alpay and published by Springer Science & Business Media. This book was released on 2006 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: The state space method developed in the last decades allows us to study the theory of linear systems by using tools from the theory of linear operators; conversely, it had a strong influence on operator theory introducing new questions and topics. The present volume contains a collection of essays representing some of the recent advances in the state space method. Methods covered include noncommutative systems theory, new aspects of the theory of discrete systems, discrete analogs of canonical systems, and new applications to the theory of Bezoutiants and convolution equations. The articles in the volume will be of interest to pure and applied mathematicians, electrical engineers and theoretical physicists.
Book Synopsis Modern Control: State-Space Analysis and Design Methods by : Arie Nakhmani
Download or read book Modern Control: State-Space Analysis and Design Methods written by Arie Nakhmani and published by McGraw Hill Professional. This book was released on 2020-05-01 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Apply a state-space approach to modern control system analysis and design Written by an expert in the field, this concise textbook offers hands-on coverage of modern control system engineering. Modern Control: State-Space Analysis and Design Methods features start-to-finish design projects as well as online snippets of MATLAB code with simulations. The essential mathematics are presented along with fully worked-out examples in gradually increasing degrees of difficulty. Readers will receive “just-in-time” math background from a comprehensive appendix and get step-by-step descriptions of the latest analysis and design techniques. Coverage includes: • An introduction to control systems • State-space representations • Pole placement via state feedback • State estimators (observers) • Non-minimal canonical forms • Linearization • Lyapunov stability • Linear quadratic regulators (LQR) • Symmetric root locus (SRL) • Kalman filter • Linear quadratic gaussian control (LQG)
Book Synopsis Linear Control Theory by : Frederick Walker Fairman
Download or read book Linear Control Theory written by Frederick Walker Fairman and published by John Wiley & Sons. This book was released on 1998-06-11 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Incorporating recent developments in control and systems research,Linear Control Theory provides the fundamental theoreticalbackground needed to fully exploit control system design software.This logically-structured text opens with a detailed treatment ofthe relevant aspects of the state space analysis of linear systems.End-of-chapter problems facilitate the learning process byencouraging the student to put his or her skills into practice.Features include: * The use of an easy to understand matrix variational technique todevelop the time-invariant quadratic and LQG controllers * A step-by-step introduction to essential mathematical ideas asthey are needed, motivating the reader to venture beyond basicconcepts * The examination of linear system theory as it relates to controltheory * The use of the PBH test to characterize eigenvalues in the statefeedback and observer problems rather than its usual role as a testfor controllability or observability * The development of model reduction via balanced realization * The employment of the L2 gain as a basis for the development ofthe H??? controller for the design of controllers in the presenceof plant model uncertainty Senior undergraduate and postgraduate control engineering studentsand practicing control engineers will appreciate the insight thisself-contained book offers into the intelligent use of today scontrol system software tools.
Book Synopsis State Space Modeling of Time Series by : Masanao Aoki
Download or read book State Space Modeling of Time Series written by Masanao Aoki and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: model's predictive capability? These are some of the questions that need to be answered in proposing any time series model construction method. This book addresses these questions in Part II. Briefly, the covariance matrices between past data and future realizations of time series are used to build a matrix called the Hankel matrix. Information needed for constructing models is extracted from the Hankel matrix. For example, its numerically determined rank will be the di mension of the state model. Thus the model dimension is determined by the data, after balancing several sources of error for such model construction. The covariance matrix of the model forecasting error vector is determined by solving a certain matrix Riccati equation. This matrix is also the covariance matrix of the innovation process which drives the model in generating model forecasts. In these model construction steps, a particular model representation, here referred to as balanced, is used extensively. This mode of model representation facilitates error analysis, such as assessing the error of using a lower dimensional model than that indicated by the rank of the Hankel matrix. The well-known Akaike's canonical correlation method for model construc tion is similar to the one used in this book. There are some important differ ences, however. Akaike uses the normalized Hankel matrix to extract canonical vectors, while the method used in this book does not normalize the Hankel ma trix.
Book Synopsis Bayesian Inference of State Space Models by : Kostas Triantafyllopoulos
Download or read book Bayesian Inference of State Space Models written by Kostas Triantafyllopoulos and published by Springer Nature. This book was released on 2021-11-12 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models. The celebrated Kalman filter, with its numerous extensions, takes centre stage in the book. Univariate and multivariate models, linear Gaussian, non-linear and non-Gaussian models are discussed with applications to signal processing, environmetrics, economics and systems engineering. Over the past years there has been a growing literature on Bayesian inference of state space models, focusing on multivariate models as well as on non-linear and non-Gaussian models. The availability of time series data in many fields of science and industry on the one hand, and the development of low-cost computational capabilities on the other, have resulted in a wealth of statistical methods aimed at parameter estimation and forecasting. This book brings together many of these methods, presenting an accessible and comprehensive introduction to state space models. A number of data sets from different disciplines are used to illustrate the methods and show how they are applied in practice. The R package BTSA, created for the book, includes many of the algorithms and examples presented. The book is essentially self-contained and includes a chapter summarising the prerequisites in undergraduate linear algebra, probability and statistics. An up-to-date and complete account of state space methods, illustrated by real-life data sets and R code, this textbook will appeal to a wide range of students and scientists, notably in the disciplines of statistics, systems engineering, signal processing, data science, finance and econometrics. With numerous exercises in each chapter, and prerequisite knowledge conveniently recalled, it is suitable for upper undergraduate and graduate courses.
Book Synopsis Time Series Analysis for the State-Space Model with R/Stan by : Junichiro Hagiwara
Download or read book Time Series Analysis for the State-Space Model with R/Stan written by Junichiro Hagiwara and published by Springer Nature. This book was released on 2021-08-30 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and concrete illustration of time series analysis focusing on the state-space model, which has recently attracted increasing attention in a broad range of fields. The major feature of the book lies in its consistent Bayesian treatment regarding whole combinations of batch and sequential solutions for linear Gaussian and general state-space models: MCMC and Kalman/particle filter. The reader is given insight on flexible modeling in modern time series analysis. The main topics of the book deal with the state-space model, covering extensively, from introductory and exploratory methods to the latest advanced topics such as real-time structural change detection. Additionally, a practical exercise using R/Stan based on real data promotes understanding and enhances the reader’s analytical capability.
Book Synopsis System Dynamics for Engineering Students by : Nicolae Lobontiu
Download or read book System Dynamics for Engineering Students written by Nicolae Lobontiu and published by Academic Press. This book was released on 2017-08-29 with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt: Engineering system dynamics focuses on deriving mathematical models based on simplified physical representations of actual systems, such as mechanical, electrical, fluid, or thermal, and on solving these models for analysis or design purposes. System Dynamics for Engineering Students: Concepts and Applications features a classical approach to system dynamics and is designed to be utilized as a one-semester system dynamics text for upper-level undergraduate students with emphasis on mechanical, aerospace, or electrical engineering. It is the first system dynamics textbook to include examples from compliant (flexible) mechanisms and micro/nano electromechanical systems (MEMS/NEMS). This new second edition has been updated to provide more balance between analytical and computational approaches; introduces additional in-text coverage of Controls; and includes numerous fully solved examples and exercises. Features a more balanced treatment of mechanical, electrical, fluid, and thermal systems than other texts Introduces examples from compliant (flexible) mechanisms and MEMS/NEMS Includes a chapter on coupled-field systems Incorporates MATLAB® and Simulink® computational software tools throughout the book Supplements the text with extensive instructor support available online: instructor's solution manual, image bank, and PowerPoint lecture slides NEW FOR THE SECOND EDITION Provides more balance between analytical and computational approaches, including integration of Lagrangian equations as another modelling technique of dynamic systems Includes additional in-text coverage of Controls, to meet the needs of schools that cover both controls and system dynamics in the course Features a broader range of applications, including additional applications in pneumatic and hydraulic systems, and new applications in aerospace, automotive, and bioengineering systems, making the book even more appealing to mechanical engineers Updates include new and revised examples and end-of-chapter exercises with a wider variety of engineering applications
Book Synopsis Fixed Interval Smoothing for State Space Models by : Howard L. Weinert
Download or read book Fixed Interval Smoothing for State Space Models written by Howard L. Weinert and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fixed-interval smoothing is a method of extracting useful information from inaccurate data. It has been applied to problems in engineering, the physical sciences, and the social sciences, in areas such as control, communications, signal processing, acoustics, geophysics, oceanography, statistics, econometrics, and structural analysis. This monograph addresses problems for which a linear stochastic state space model is available, in which case the objective is to compute the linear least-squares estimate of the state vector in a fixed interval, using observations previously collected in that interval. The author uses a geometric approach based on the method of complementary models. Using the simplest possible notation, he presents straightforward derivations of the four types of fixed-interval smoothing algorithms, and compares the algorithms in terms of efficiency and applicability. Results show that the best algorithm has received the least attention in the literature. Fixed Interval Smoothing for State Space Models: includes new material on interpolation, fast square root implementations, and boundary value models; is the first book devoted to smoothing; contains an annotated bibliography of smoothing literature; uses simple notation and clear derivations; compares algorithms from a computational perspective; identifies a best algorithm. Fixed Interval Smoothing for State Space Models will be the primary source for those wanting to understand and apply fixed-interval smoothing: academics, researchers, and graduate students in control, communications, signal processing, statistics and econometrics.
Book Synopsis Forecasting with Exponential Smoothing by : Rob Hyndman
Download or read book Forecasting with Exponential Smoothing written by Rob Hyndman and published by Springer Science & Business Media. This book was released on 2008-06-19 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exponential smoothing methods have been around since the 1950s, and are still the most popular forecasting methods used in business and industry. However, a modeling framework incorporating stochastic models, likelihood calculation, prediction intervals and procedures for model selection, was not developed until recently. This book brings together all of the important new results on the state space framework for exponential smoothing. It will be of interest to people wanting to apply the methods in their own area of interest as well as for researchers wanting to take the ideas in new directions. Part 1 provides an introduction to exponential smoothing and the underlying models. The essential details are given in Part 2, which also provide links to the most important papers in the literature. More advanced topics are covered in Part 3, including the mathematical properties of the models and extensions of the models for specific problems. Applications to particular domains are discussed in Part 4.
Book Synopsis State-Space Control Systems by : Farzin Asadi
Download or read book State-Space Control Systems written by Farzin Asadi and published by Morgan & Claypool Publishers. This book was released on 2020-10-05 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: These days, nearly all the engineering problem are solved with the aid of suitable computer packages. This book shows how MATLAB/Simulink could be used to solve state-space control problems. In this book, it is assumed that you are familiar with the theory and concepts of state-space control, i.e., you took or you are taking a course on state-space control system and you read this book in order to learn how to solve state-space control problems with the aid of MATLAB/Simulink. The book is composed of three chapters. Chapter 1 shows how a state-space mathematical model could be entered into the MATLAB/Simulink environment. Chapter 2 shows how a nonlinear system could be linearized around the desired operating point with the aid of tools provided by MATLAB/Simulink. Finally, Chapter 3 shows how a state-space controller could be designed with the aid MATLAB and be tested with Simulink. The book will be useful for students and practical engineers who want to design a state-space control system.
Book Synopsis State Space Grids by : Tom Hollenstein
Download or read book State Space Grids written by Tom Hollenstein and published by Springer Science & Business Media. This book was released on 2012-10-28 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human development from birth through adulthood is a complex interplay of many interacting forces. Children’s internal processes are manifest in behaviors that are sculpted by their experiences, most notably with primary caregivers. Because the discipline of psychology explores human behavior and cognition, the techniques employed for developmental analysis must be able to describe, depict, and quantify these complex processes. State Space Grids provides the framework, basic method, rationale, and advanced techniques for translating the behavior of children, adolescents, and parents into visible, traceable data. This seminar-between-covers takes readers step by step from conceptualization through implementation of projects, with examples from a range of current research within and outside child development. Links are included for the GridWare software program and related user resources. And although state space grids need not be used only to analyze dynamic systems, they serve as an excellent tool for honing systemic thinking. Key coverage in this volume includes: Dynamic systems and the origins of state space grids. The state of research using state space grids. Introducing GridWare and how it works. How to use state space grids, from idea through finished project. Within-grid and between-grid analysis. Conducting advanced analysis. State Space Grids is an essential reference for researchers across such disciplines as psychology, neuroscience, economics, computer science, and agricultural science.
Book Synopsis Machine Learning for Model Order Reduction by : Khaled Salah Mohamed
Download or read book Machine Learning for Model Order Reduction written by Khaled Salah Mohamed and published by Springer. This book was released on 2018-03-02 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Book discusses machine learning for model order reduction, which can be used in modern VLSI design to predict the behavior of an electronic circuit, via mathematical models that predict behavior. The author describes techniques to reduce significantly the time required for simulations involving large-scale ordinary differential equations, which sometimes take several days or even weeks. This method is called model order reduction (MOR), which reduces the complexity of the original large system and generates a reduced-order model (ROM) to represent the original one. Readers will gain in-depth knowledge of machine learning and model order reduction concepts, the tradeoffs involved with using various algorithms, and how to apply the techniques presented to circuit simulations and numerical analysis. Introduces machine learning algorithms at the architecture level and the algorithm levels of abstraction; Describes new, hybrid solutions for model order reduction; Presents machine learning algorithms in depth, but simply; Uses real, industrial applications to verify algorithms.
