Frequency Domain and State Space Methods for Linear Systems PDF Download

Author: Christopher I. Byrnes
Publisher: North Holland
ISBN:
Category : Computers
Languages : en
Pages : 580

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Book Description
Very Good,No Highlights or Markup,all pages are intact.

Author: Bernard Friedland
Publisher: Courier Corporation
ISBN: 048613511X
Category : Science
Languages : en
Pages : 530

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Book Description
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.

Author: Robert L. Williams, II
Publisher: John Wiley & Sons
ISBN: 0471735558
Category : Technology & Engineering
Languages : en
Pages : 485

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Book Description
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.

Author: Chung-Wen Chen
Publisher:
ISBN:
Category :
Languages : en
Pages : 24

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Book Description

Author: John S. Bay
Publisher: McGraw-Hill Science, Engineering & Mathematics
ISBN:
Category : Mathematics
Languages : en
Pages : 600

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Book Description
Spans a broad range of linear system theory concepts, but does so in a complete and sequential style. It is suitable for a first-year graduate or advanced undergraduate course in any field of engineering. State space methods are derived from first principles while drawing on the students' previous understanding of physical and mathematical concepts. The text requires only a knowledge of basic signals and systems theory, but takes the student, in a single semester, all the way through state feedback, observers, Kalman filters, and elementary I.Q.G. control.

Author: Khaled Salah Mohamed
Publisher:
ISBN: 9783319757155
Category : Integrated circuits
Languages : en
Pages : 93

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Book Description
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.

Author: Philip E. Sarachik
Publisher: Cambridge University Press
ISBN: 9780521570572
Category : Technology & Engineering
Languages : en
Pages : 294

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Book Description
State-space methods form the basis of modern control theory. This textbook is devoted to a description of these methods in the analysis of linear multi-input, multi-output dynamic systems. Following a chapter that sets out the basic concepts and definitions, the author discusses state equations of finite dimensional systems and their solution. He then presents the principles of time-domain and frequency-domain analysis, and the properties and applications of the Z-transformation. Separate chapters deal with the controllability, observability, and stability of linear systems. The appendix offers a useful tutorial review of the key results from matrix theory and linear algebra. The book includes several worked examples, and there are problems at the end of each chapter. It will be of great use to advanced undergraduate and graduate students of electrical or mechanical engineering taking courses in linear systems or control systems.

Author: Stephen P. Banks
Publisher:
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 140

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Book Description

Author: Peter van Overschee
Publisher: Springer Science & Business Media
ISBN: 1461304652
Category : Technology & Engineering
Languages : en
Pages : 263

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Book Description
Subspace Identification for Linear Systems focuses on the theory, implementation and applications of subspace identification algorithms for linear time-invariant finite- dimensional dynamical systems. These algorithms allow for a fast, straightforward and accurate determination of linear multivariable models from measured input-output data. The theory of subspace identification algorithms is presented in detail. Several chapters are devoted to deterministic, stochastic and combined deterministic-stochastic subspace identification algorithms. For each case, the geometric properties are stated in a main 'subspace' Theorem. Relations to existing algorithms and literature are explored, as are the interconnections between different subspace algorithms. The subspace identification theory is linked to the theory of frequency weighted model reduction, which leads to new interpretations and insights. The implementation of subspace identification algorithms is discussed in terms of the robust and computationally efficient RQ and singular value decompositions, which are well-established algorithms from numerical linear algebra. The algorithms are implemented in combination with a whole set of classical identification algorithms, processing and validation tools in Xmath's ISID, a commercially available graphical user interface toolbox. The basic subspace algorithms in the book are also implemented in a set of Matlab files accompanying the book. An application of ISID to an industrial glass tube manufacturing process is presented in detail, illustrating the power and user-friendliness of the subspace identification algorithms and of their implementation in ISID. The identified model allows for an optimal control of the process, leading to a significant enhancement of the production quality. The applicability of subspace identification algorithms in industry is further illustrated with the application of the Matlab files to ten practical problems. Since all necessary data and Matlab files are included, the reader can easily step through these applications, and thus get more insight in the algorithms. Subspace Identification for Linear Systems is an important reference for all researchers in system theory, control theory, signal processing, automization, mechatronics, chemical, electrical, mechanical and aeronautical engineering.

Author: Maurício C. de Oliveira
Publisher: Cambridge University Press
ISBN: 1316949907
Category : Technology & Engineering
Languages : en
Pages : 317

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Book Description
Taking a different approach from standard thousand-page reference-style control textbooks, Fundamentals of Linear Control provides a concise yet comprehensive introduction to the analysis and design of feedback control systems in fewer than 400 pages. The text focuses on classical methods for dynamic linear systems in the frequency domain. The treatment is, however, modern and the reader is kept aware of contemporary tools and techniques, such as state space methods and robust and nonlinear control. Featuring fully worked design examples, richly illustrated chapters, and an extensive set of homework problems and examples spanning across the text for gradual challenge and perspective, this textbook is an excellent choice for senior-level courses in systems and control or as a complementary reference in introductory graduate level courses. The text is designed to appeal to a broad audience of engineers and scientists interested in learning the main ideas behind feedback control theory.