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Multivariable Feedback Control

Multivariable Feedback Control

Author: Sigurd Skogestad

Publisher: John Wiley & Sons Incorporated

ISBN: UOM:39015062583094

Category: Science

Page: 600

View: 726

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An introduction to the analysis & design of robust multivariable control, concentrating on practical feedback control rather than system theory in general.

Linear and Nonlinear Multivariable Feedback Control

Linear and Nonlinear Multivariable Feedback Control

Author: Oleg Gasparyan

Publisher: John Wiley & Sons

ISBN: 9780470061046

Category: Science

Page: 341

View: 628

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"Linear and Nonlinear Multivariable Feedback Control presents a highly original, unified control theory of both linear and nonlinear multivariable (also known as multi-input multi-output (MIMO)) feedback systems as a straightforward extension of classical control theory. It shows how the classical engineering methods look in the multidimensional case and how practising engineers or researchers can apply them to the analysis and design of linear and nonlinear MIMO systems."--BOOK JACKET.

Design of Linear Multivariable Feedback Control Systems

Design of Linear Multivariable Feedback Control Systems

Author: Joseph J. Bongiorno Jr.

Publisher: Springer Nature

ISBN: 9783030443566

Category: Technology & Engineering

Page: 453

View: 251

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This book contains a derivation of the subset of stabilizing controllers for analog and digital linear time-invariant multivariable feedback control systems that insure stable system errors and stable controller outputs for persistent deterministic reference inputs that are trackable and for persistent deterministic disturbance inputs that are rejectable. For this subset of stabilizing controllers, the Wiener-Hopf methodology is then employed to obtain the optimal controller for which a quadratic performance measure is minimized. This is done for the completely general standard configuration and methods that enable the trading off of optimality for an improved stability margin and/or reduced sensitivity to plant model uncertainty are described. New and novel results on the optimal design of decoupled (non-interacting) systems are also presented. The results are applied in two examples: the one- and three-degree-of-freedom configurations. These demonstrate that the standard configuration is one encompassing all possible feedback configurations. Each chapter is completed by a group of worked examples, which reveal additional insights and extensions of the theory presented in the chapter. Three of the examples illustrate the application of the theory to two physical cases: the depth and pitch control of a submarine and the control of a Rosenbrock process. In the latter case, designs with and without decoupling are compared. This book provides researchers and graduate students working in feedback control with a valuable reference for Wiener–Hopf theory of multivariable design. Basic knowledge of linear systems and matrix theory is required.

Multivariable Feedback Control

Multivariable Feedback Control

Author: Sigurd Skogestad

Publisher: John Wiley & Sons

ISBN: UOM:39015037846493

Category: Engineering, General

Page: 559

View: 384

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Numerous worked examples, exercises and case studies, which make frequent use of MATLAB, are included. MATLAB files for examples and figures, solutions to selected exercises, extra problems and linear state-space models for the case studies are available on the Internet.

Design of Multivariable Feedback Control Systems Via Spectral Assignment Using Reduced-order Models and Reduced-order Observers

Design of Multivariable Feedback Control Systems Via Spectral Assignment Using Reduced-order Models and Reduced-order Observers

Author: Roland R. Mielke

Publisher:

ISBN: NASA:31769000509649

Category: Feedback control systems

Page: 147

View: 582

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The feasibility of using reduced order models and reduced order observers with eigenvalue/eigenvector assignment procedures is investigated. A review of spectral assignment synthesis procedures is presented. Then, a reduced order model which retains essential system characteristics is formulated. A constant state feedback matrix which assigns desired closed loop eigenvalues and approximates specified closed loop eigenvectors is calculated for the reduced order model. It is shown that the eigenvalue and eigenvector assignments made in the reduced order system are retained when the feedback matrix is implemented about the full order system. In addition, those modes and associated eigenvectors which are not included in the reduced order model remain unchanged in the closed loop full order system. The fulll state feedback design is then implemented by using a reduced order observer. It is shown that the eigenvalue and eigenvector assignments of the closed loop full order system remain unchanged when a reduced order observer is used. The design procedure is illustrated by an actual design problem.

Linear Feedback Control

Linear Feedback Control

Author: Dingyu Xue

Publisher: SIAM

ISBN: 9780898716382

Category: Mathematics

Page: 354

View: 659

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Less mathematics and more working examples make this textbook suitable for almost any type of user.

Multivariable Feedback Systems

Multivariable Feedback Systems

Author: F. M. Callier

Publisher: Springer

ISBN: UCAL:B4534873

Category: Mathematics

Page: 296

View: 446

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This volume is the result of our teaching in the last few years of a first year graduate course on multivariable feedback systems addressed to control engineers. The prerequisites are modest: an undergraduate course in control (for acquaintance with concepts, terms, and design goals) and a senior-graduate course in linear systems. This volume covers lumped linear time-invariant multi-input multi-output systems with strong emphasis on control problems. The purpose is to provide a rapid introduction to some of the main and simpler results of control theory and to provide access to the current literature. Note that our exposition pays particular attention to the time-domain behavior of the systems under study. Note also that we cover neither optimization nor stochastic systems since these topics are treated in separate courses. As is obvious from its abundant literature, multivariable control is a very rapidly developing field. Consequently, we have no expectation that our exposition will become definitive; however, we hope that our efforts will be found useful. To get an idea of the contents, we suggest reading carefully the table of contents and the introduction of the chapters. Roughly, Chapter 1 is an introduction to feedback issues in a multivariable context (desensitization, large gain, singular values, etc. ). Chapters 2 and 3 cover the mathematical tools for handling transfer functions as polynomial-matrix fractions and for studying systems described by polynomial matrices. Chapter 4 uses these tools to cover the general theory of interconnected systems.

Introduction to Process Control, Third Edition

Introduction to Process Control, Third Edition

Author: Jose A. Romagnoli

Publisher: CRC Press

ISBN: 9781000078954

Category: Science

Page: 712

View: 484

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Introduction to Process Control, Third Edition continues to provide a bridge between traditional and modern views of process control by blending conventional topics with a broader perspective of integrated process operation, control, and information systems. Updated and expanded throughout, this third edition addresses issues highly relevant to today’s teaching of process control: Discusses smart manufacturing, new data preprocessing techniques, and machine learning and artificial intelligence concepts that are part of current smart manufacturing decisions Includes extensive references to guide the reader to the resources needed to solve modeling, classification, and monitoring problems Introduces the link between process optimization and process control (optimizing control), including the effect of disturbances on the optimal plant operation, the concepts of steady-state and dynamic back-off as ways to quantify the economic benefits of control, and how to determine an optimal transition policy during a planned production change Incorporates an introduction to the modern architectures of industrial computer control systems with real case studies and applications to pilot-scale operations Analyzes the expanded role of process control in modern manufacturing, including model-centric technologies and integrated control systems Integrates data processing/reconciliation and intelligent monitoring in the overall control system architecture Drawing on the authors’ combined 60 years of teaching experiences, this classroom-tested text is designed for chemical engineering students but is also suitable for industrial practitioners who need to understand key concepts of process control and how to implement them. The text offers a comprehensive pedagogical approach to reinforce learning and presents a concept first followed by an example, allowing students to grasp theoretical concepts in a practical manner and uses the same problem in each chapter, culminating in a complete control design strategy. A vast number of exercises throughout ensure readers are supported in their learning and comprehension. Downloadable MATLAB® toolboxes for process control education as well as the main simulation examples from the book offer a user-friendly software environment for interactively studying the examples in the text. These can be downloaded from the publisher’s website. Solutions manual is available for qualifying professors from the publisher.

Feedback Control of MEMS to Atoms

Feedback Control of MEMS to Atoms

Author: Jason J. Gorman

Publisher: Springer Science & Business Media

ISBN: 9781441958310

Category: Technology & Engineering

Page: 384

View: 170

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Control from MEMS to Atoms illustrates the use of control and control systems as an essential part of functioning integrated systems. The book is organized according to the dimensional scale of the problem, starting with micro-scale systems and ending with atomic-scale systems. Similar to macro-scale machines and processes, control systems can play a major role in improving the performance of micro- and nano-scale systems and in enabling new capabilities that would otherwise not be possible. However, the majority of problems at these scales present many new challenges that go beyond the current state-of-the-art in control engineering. This is a result of the multidisciplinary nature of micro/nanotechnology, which requires the merging of control engineering with physics, biology and chemistry.