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Control System Design

2012-03-08 Science
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Release : 2012-03-08
Genre : Science
Kind : eBook
Book Rating : 11X/5 ( reviews)

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Book Synopsis Control System Design by : Bernard Friedland

Download or read book Control System Design written by Bernard Friedland. This book was released on 2012-03-08. 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.

Linear State-Space Control Systems

2007-02-09 Technology & Engineering
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Release : 2007-02-09
Genre : Technology & Engineering
Kind : eBook
Book Rating : 558/5 ( reviews)

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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. This book was released on 2007-02-09. 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.

State-Space Methods for Time Series Analysis

2018-09-03 Mathematics
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Release : 2018-09-03
Genre : Mathematics
Kind : eBook
Book Rating : 25X/5 ( reviews)

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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. This book was released on 2018-09-03. 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.

Modern Control: State-Space Analysis and Design Methods

2020-05-01 Technology & Engineering
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Release : 2020-05-01
Genre : Technology & Engineering
Kind : eBook
Book Rating : 25X/5 ( reviews)

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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. This book was released on 2020-05-01. 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)

Time Series Analysis by State Space Methods

2012-05-03 Business & Economics
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Release : 2012-05-03
Genre : Business & Economics
Kind : eBook
Book Rating : 194/5 ( reviews)

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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. This book was released on 2012-05-03. 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.

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