State-Space System Realization with Input- and Output-Data Correlation

State-Space System Realization with Input- and Output-Data Correlation PDF Author: Jer-Nan Juang
Publisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 48

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State-Space System Realization with Input- and Output-Data Correlation

State-Space System Realization with Input- and Output-Data Correlation PDF Author: Jer-Nan Juang
Publisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 48

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Linear State-Space Control Systems

Linear State-Space Control Systems PDF 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.

State-Space System Realization with Input- And Output-Data Correlation

State-Space System Realization with Input- And Output-Data Correlation PDF Author: National Aeronautics and Space Administration (NASA)
Publisher: Createspace Independent Publishing Platform
ISBN: 9781722799847
Category :
Languages : en
Pages : 44

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Book Description
This paper introduces a general version of the information matrix consisting of the autocorrelation and cross-correlation matrices of the shifted input and output data. Based on the concept of data correlation, a new system realization algorithm is developed to create a model directly from input and output data. The algorithm starts by computing a special type of correlation matrix derived from the information matrix. The special correlation matrix provides information on the system-observability matrix and the state-vector correlation. A system model is then developed from the observability matrix in conjunction with other algebraic manipulations. This approach leads to several different algorithms for computing system matrices for use in representing the system model. The relationship of the new algorithms with other realization algorithms in the time and frequency domains is established with matrix factorization of the information matrix. Several examples are given to illustrate the validity and usefulness of these new algorithms. Juang, Jer-Nan Langley Research Center RTOP 233-10-14-03...

Subspace Identification for Linear Systems

Subspace Identification for Linear Systems PDF 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.

Scientific and Technical Aerospace Reports

Scientific and Technical Aerospace Reports PDF Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 316

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NASA Technical Paper

NASA Technical Paper PDF Author:
Publisher:
ISBN:
Category : Astronautics
Languages : en
Pages : 486

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Introduction to PID Controllers

Introduction to PID Controllers PDF Author: Rames C. Panda
Publisher: BoD – Books on Demand
ISBN: 9533079274
Category : Technology & Engineering
Languages : en
Pages : 274

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Book Description
This book discusses the theory, application, and practice of PID control technology. It is designed for engineers, researchers, students of process control, and industry professionals. It will also be of interest for those seeking an overview of the subject of green automation who need to procure single loop and multi-loop PID controllers and who aim for an exceptional, stable, and robust closed-loop performance through process automation. Process modeling, controller design, and analyses using conventional and heuristic schemes are explained through different applications here. The readers should have primary knowledge of transfer functions, poles, zeros, regulation concepts, and background. The following sections are covered: The Theory of PID Controllers and their Design Methods, Tuning Criteria, Multivariable Systems: Automatic Tuning and Adaptation, Intelligent PID Control, Discrete, Intelligent PID Controller, Fractional Order PID Controllers, Extended Applications of PID, and Practical Applications. A wide variety of researchers and engineers seeking methods of designing and analyzing controllers will create a heavy demand for this book: interdisciplinary researchers, real time process developers, control engineers, instrument technicians, and many more entities that are recognizing the value of shifting to PID controller procurement.

European Control Conference 1991

European Control Conference 1991 PDF Author:
Publisher: European Control Association
ISBN: 9782866012816
Category : Control theory
Languages : en
Pages : 1012

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Book Description
Proceedings of the European Control Conference 1991, July 2-5, 1991, Grenoble, France

National Specialists Meeting

National Specialists Meeting PDF Author:
Publisher:
ISBN:
Category : Helicopters
Languages : en
Pages : 540

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Subspace Methods for System Identification

Subspace Methods for System Identification PDF Author: Tohru Katayama
Publisher: Springer Science & Business Media
ISBN: 184628158X
Category : Technology & Engineering
Languages : en
Pages : 400

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Book Description
An in-depth introduction to subspace methods for system identification in discrete-time linear systems thoroughly augmented with advanced and novel results, this text is structured into three parts. Part I deals with the mathematical preliminaries: numerical linear algebra; system theory; stochastic processes; and Kalman filtering. Part II explains realization theory as applied to subspace identification. Stochastic realization results based on spectral factorization and Riccati equations, and on canonical correlation analysis for stationary processes are included. Part III demonstrates the closed-loop application of subspace identification methods. Subspace Methods for System Identification is an excellent reference for researchers and a useful text for tutors and graduate students involved in control and signal processing courses. It can be used for self-study and will be of interest to applied scientists or engineers wishing to use advanced methods in modeling and identification of complex systems.