System Identification With Matlab

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Principles of System Identification

Author : Arun K. Tangirala
Publisher : CRC Press
ISBN 13 : 143989602X
Total Pages : 908 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Principles of System Identification by : Arun K. Tangirala

Download or read book Principles of System Identification written by Arun K. Tangirala and published by CRC Press. This book was released on 2018-10-08 with total page 908 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master Techniques and Successfully Build Models Using a Single Resource Vital to all data-driven or measurement-based process operations, system identification is an interface that is based on observational science, and centers on developing mathematical models from observed data. Principles of System Identification: Theory and Practice is an introductory-level book that presents the basic foundations and underlying methods relevant to system identification. The overall scope of the book focuses on system identification with an emphasis on practice, and concentrates most specifically on discrete-time linear system identification. Useful for Both Theory and Practice The book presents the foundational pillars of identification, namely, the theory of discrete-time LTI systems, the basics of signal processing, the theory of random processes, and estimation theory. It explains the core theoretical concepts of building (linear) dynamic models from experimental data, as well as the experimental and practical aspects of identification. The author offers glimpses of modern developments in this area, and provides numerical and simulation-based examples, case studies, end-of-chapter problems, and other ample references to code for illustration and training. Comprising 26 chapters, and ideal for coursework and self-study, this extensive text: Provides the essential concepts of identification Lays down the foundations of mathematical descriptions of systems, random processes, and estimation in the context of identification Discusses the theory pertaining to non-parametric and parametric models for deterministic-plus-stochastic LTI systems in detail Demonstrates the concepts and methods of identification on different case-studies Presents a gradual development of state-space identification and grey-box modeling Offers an overview of advanced topics of identification namely the linear time-varying (LTV), non-linear, and closed-loop identification Discusses a multivariable approach to identification using the iterative principal component analysis Embeds MATLAB® codes for illustrated examples in the text at the respective points Principles of System Identification: Theory and Practice presents a formal base in LTI deterministic and stochastic systems modeling and estimation theory; it is a one-stop reference for introductory to moderately advanced courses on system identification, as well as introductory courses on stochastic signal processing or time-series analysis.The MATLAB scripts and SIMULINK models used as examples and case studies in the book are also available on the author's website: http://arunkt.wix.com/homepage#!textbook/c397

Mastering System Identification in 100 Exercises

Author : Johan Schoukens
Publisher : John Wiley & Sons
ISBN 13 : 1118218507
Total Pages : 285 pages
Book Rating : 4.1/5 (182 download)

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Book Synopsis Mastering System Identification in 100 Exercises by : Johan Schoukens

Download or read book Mastering System Identification in 100 Exercises written by Johan Schoukens and published by John Wiley & Sons. This book was released on 2012-04-02 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book enables readers to understand system identification and linear system modeling through 100 practical exercises without requiring complex theoretical knowledge. The contents encompass state-of-the-art system identification methods, with both time and frequency domain system identification methods covered, including the pros and cons of each. Each chapter features MATLAB exercises, discussions of the exercises, accompanying MATLAB downloads, and larger projects that serve as potential assignments in this learn-by-doing resource.

Flight Vehicle System Identification

Author : Ravindra V. Jategaonkar
Publisher : AIAA (American Institute of Aeronautics & Astronautics)
ISBN 13 :
Total Pages : 568 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Flight Vehicle System Identification by : Ravindra V. Jategaonkar

Download or read book Flight Vehicle System Identification written by Ravindra V. Jategaonkar and published by AIAA (American Institute of Aeronautics & Astronautics). This book was released on 2006 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: This valuable volume offers a systematic approach to flight vehicle system identification and exhaustively covers the time domain methodology. It addresses in detail the theoretical and practical aspects of various parameter estimation methods, including those in the stochastic framework and focusing on nonlinear models, cost functions, optimization methods, and residual analysis. A pragmatic and balanced account of pros and cons in each case is provided. The book also presents data gathering and model validation, and covers both large-scale systems and high-fidelity modeling. Real world problems dealing with a variety of flight vehicle applications are addressed and solutions are provided. Examples encompass such problems as estimation of aerodynamics, stability, and control derivatives from flight data, flight path reconstruction, nonlinearities in control surface effectiveness, stall hysteresis, unstable aircraft, and other critical considerations.

Aircraft System Identification

Author : Eugene Morelli
Publisher : Sunflyte Enterprises
ISBN 13 : 9780997430615
Total Pages : 618 pages
Book Rating : 4.4/5 (36 download)

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Book Synopsis Aircraft System Identification by : Eugene Morelli

Download or read book Aircraft System Identification written by Eugene Morelli and published by Sunflyte Enterprises. This book was released on 2016 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of both the theoretical underpinnings and the practical application of aircraft modeling based on experimental data also known as aircraft system identification. Much of the material presented comes from the authors own extensive research and teaching activities at the NASA Langley Research Center, and is based on real-world applications of system identification to aircraft. The book uses actual flight-test and wind-tunnel data for case studies and examples, and is a valuable resource for researchers and practicing engineers, as well as a textbook for postgraduate and senior-level courses. [...] The methods and algorithms explained in the book are implemented in a NASA software toolbox called SIDPAC (System IDentification Programs for AirCraft). SIDPAC is written in MATLAB®, and is available by request from NASA Langley Research Center. SIDPAC is composed of many different tools that implement a wide variety of approaches explained fully in the book. These tools can be readily applied to solve aircraft system identification problems.

System Identification

Author : Rik Pintelon
Publisher : John Wiley & Sons
ISBN 13 : 0471660957
Total Pages : 644 pages
Book Rating : 4.4/5 (716 download)

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Book Synopsis System Identification by : Rik Pintelon

Download or read book System Identification written by Rik Pintelon and published by John Wiley & Sons. This book was released on 2004-04-05 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: Electrical Engineering System Identification A Frequency Domain Approach How does one model a linear dynamic system from noisy data? This book presents a general approach to this problem, with both practical examples and theoretical discussions that give the reader a sound understanding of the subject and of the pitfalls that might occur on the road from raw data to validated model. The emphasis is on robust methods that can be used with a minimum of user interaction. Readers in many fields of engineering will gain knowledge about: * Choice of experimental setup and experiment design * Automatic characterization of disturbing noise * Generation of a good plant model * Detection, qualification, and quantification of nonlinear distortions * Identification of continuous- and discrete-time models * Improved model validation tools and from the theoretical side about: * System identification * Interrelations between time- and frequency-domain approaches * Stochastic properties of the estimators * Stochastic analysis System Identification: A Frequency Domain Approach is written for practicing engineers and scientists who do not want to delve into mathematical details of proofs. Also, it is written for researchers who wish to learn more about the theoretical aspects of the proofs. Several of the introductory chapters are suitable for undergraduates. Each chapter begins with an abstract and ends with exercises, and examples are given throughout.

System Identification

Author : Lennart Ljung
Publisher : Pearson Education
ISBN 13 : 0132440539
Total Pages : 875 pages
Book Rating : 4.1/5 (324 download)

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Book Synopsis System Identification by : Lennart Ljung

Download or read book System Identification written by Lennart Ljung and published by Pearson Education. This book was released on 1998-12-29 with total page 875 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field's leading text, now completely updated. Modeling dynamical systems — theory, methodology, and applications. Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and general non-linear black box methods, including neural networks and neuro-fuzzy modeling. The book contains many new computer-based examples designed for Ljung's market-leading software, System Identification Toolbox for MATLAB. Ljung combines careful mathematics, a practical understanding of real-world applications, and extensive exercises. He introduces both black-box and tailor-made models of linear as well as non-linear systems, and he describes principles, properties, and algorithms for a variety of identification techniques: Nonparametric time-domain and frequency-domain methods. Parameter estimation methods in a general prediction error setting. Frequency domain data and frequency domain interpretations. Asymptotic analysis of parameter estimates. Linear regressions, iterative search methods, and other ways to compute estimates. Recursive (adaptive) estimation techniques. Ljung also presents detailed coverage of the key issues that can make or break system identification projects, such as defining objectives, designing experiments, controlling the bias distribution of transfer-function estimates, and carefully validating the resulting models. The first edition of System Identification has been the field's most widely cited reference for over a decade. This new edition will be the new text of choice for anyone concerned with system identification theory and practice.

Basic System Identification with MATLAB

Author : Kendall T.
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781539772279
Total Pages : 222 pages
Book Rating : 4.7/5 (722 download)

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Book Synopsis Basic System Identification with MATLAB by : Kendall T.

Download or read book Basic System Identification with MATLAB written by Kendall T. and published by Createspace Independent Publishing Platform. This book was released on 2016-10-27 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: System Identification Toolbox constructs mathematical models of dynamic systems from measured input-output data. It provides MATLAB(r) functions, Simulink blocks, and an interactive tool for creating and using models of dynamic systems not easily modeled from first principles or specifications You can use time-domain and frequency-domain input-output data to identify continuous-time and discrete-time transfer functions, process odels, and state-space models. The toolbox provides maximum likelihood, prediction-error minimization (PEM), subspace system identification, and other identification techniques.For nonlinear system dynamics, you can estimate Hammerstein-Weiner models and nonlinear ARX models with wavelet network, tree-partition, and sigmoid network nonlinearities. The toolbox performs grey-box system identification for estimating parameters of a user-defined model. You can use the identified model for prediction of system response and for simulation in Simulink. The toolbox also lets you model time-series data and perform time-series forecasting. The more important content in this book is the next:* Transfer function, process model, and state-space model identification using time-domain and frequency-domain response data* Autoregressive (ARX, ARMAX), Box-Jenkins, and Output-Error model estimation using maximum likelihood, prediction-error minimization(PEM), and subspace system identification techniques * Time-series modeling (AR, ARMA, ARIMA) and forecasting* Identification of nonlinear ARX models and Hammerstein-Weiner models with input-output nonlinearities such as saturation and dead zone* Linear and nonlinear grey-box system identification for estimation of user-defined models* Delay estimation, detrending, filtering, resampling, and reconstruction of missing data

Multivariable System Identification For Process Control

Author : Y. Zhu
Publisher : Elsevier
ISBN 13 : 0080537111
Total Pages : 373 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Multivariable System Identification For Process Control by : Y. Zhu

Download or read book Multivariable System Identification For Process Control written by Y. Zhu and published by Elsevier. This book was released on 2001-10-08 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems and control theory has experienced significant development in the past few decades. New techniques have emerged which hold enormous potential for industrial applications, and which have therefore also attracted much interest from academic researchers. However, the impact of these developments on the process industries has been limited.The purpose of Multivariable System Identification for Process Control is to bridge the gap between theory and application, and to provide industrial solutions, based on sound scientific theory, to process identification problems. The book is organized in a reader-friendly way, starting with the simplest methods, and then gradually introducing more complex techniques. Thus, the reader is offered clear physical insight without recourse to large amounts of mathematics. Each method is covered in a single chapter or section, and experimental design is explained before any identification algorithms are discussed. The many simulation examples and industrial case studies demonstrate the power and efficiency of process identification, helping to make the theory more applicable. MatlabTM M-files, designed to help the reader to learn identification in a computing environment, are included.

System Identification with MATLAB. Linear Models

Author : Marvin L.
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781539691891
Total Pages : 456 pages
Book Rating : 4.6/5 (918 download)

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Book Synopsis System Identification with MATLAB. Linear Models by : Marvin L.

Download or read book System Identification with MATLAB. Linear Models written by Marvin L. and published by Createspace Independent Publishing Platform. This book was released on 2016-10-23 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: In System Identification Toolbox software, MATLAB represents linear systems as model objects. Model objects are specialized data containers that encapsulate model data and other attributes in a structured way. Model objects allow you to manipulate linear systems as single entities rather than keeping track of multiple data vectors, matrices, or cell arrays. Model objects can represent single-input, single-output (SISO) systems or multiple-input, multiple-output (MIMO) systems. You can represent both continuous- and discrete-time linear systems. The toolbox provides several linear and nonlinear black-box model structures, which have traditionally been useful for representing dynamic systems. This book develops the next tasks with linear models:* "Black-Box Modeling" * "Identifying Frequency-Response Models" * "Identifying Impulse-Response Models" * "Identifying Process Models" * "Identifying Input-Output Polynomial Models" * "Identifying State-Space Models" * "Identifying Transfer Function Models" * "Refining Linear Parametric Models"* "Refine ARMAX Model with Initial Parameter Guesses at Command Line"* "Refine Initial ARMAX Model at Command Line" * "Extracting Numerical Model Data" * "Transforming Between Discrete-Time and Continuous-Time Representations" * "Continuous-Discrete Conversion Methods" * "Effect of Input Intersample Behavior on Continuous-Time Models" * "Transforming Between Linear Model Representations" * "Subreferencing Models"* "Concatenating Models" * "Merging Models"* "Building and Estimating Process Models Using System Identification Toolbox* "Determining Model Order and Delay" 5* "Model Structure Selection: Determining Model Order and Input Delay" * "Frequency Domain Identification: Estimating Models Using Frequency Domain Data" * "Building Structured and User-Defined Models Using System Identification Toolbox"

Filtering and System Identification

Author : Michel Verhaegen
Publisher : Cambridge University Press
ISBN 13 : 9781107405028
Total Pages : 0 pages
Book Rating : 4.4/5 (5 download)

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Book Synopsis Filtering and System Identification by : Michel Verhaegen

Download or read book Filtering and System Identification written by Michel Verhaegen and published by Cambridge University Press. This book was released on 2012-07-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Filtering and system identification are powerful techniques for building models of complex systems. This 2007 book discusses the design of reliable numerical methods to retrieve missing information in models derived using these techniques. Emphasis is on the least squares approach as applied to the linear state-space model, and problems of increasing complexity are analyzed and solved within this framework, starting with the Kalman filter and concluding with the estimation of a full model, noise statistics and state estimator directly from the data. Key background topics, including linear matrix algebra and linear system theory, are covered, followed by different estimation and identification methods in the state-space model. With end-of-chapter exercises, MATLAB simulations and numerous illustrations, this book will appeal to graduate students and researchers in electrical, mechanical and aerospace engineering. It is also useful for practitioners. Additional resources for this title, including solutions for instructors, are available online at www.cambridge.org/9780521875127.

Subspace Identification for Linear Systems

Author : Peter van Overschee
Publisher : Springer Science & Business Media
ISBN 13 : 1461304652
Total Pages : 263 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Subspace Identification for Linear Systems by : Peter van Overschee

Download or read book Subspace Identification for Linear Systems written by Peter van Overschee and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Nonlinear System Identification

Author : Stephen A. Billings
Publisher : John Wiley & Sons
ISBN 13 : 1118535553
Total Pages : 611 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Nonlinear System Identification by : Stephen A. Billings

Download or read book Nonlinear System Identification written by Stephen A. Billings and published by John Wiley & Sons. This book was released on 2013-07-29 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) model The orthogonal least squares algorithm that allows models to be built term by term where the error reduction ratio reveals the percentage contribution of each model term Statistical and qualitative model validation methods that can be applied to any model class Generalised frequency response functions which provide significant insight into nonlinear behaviours A completely new class of filters that can move, split, spread, and focus energy The response spectrum map and the study of sub harmonic and severely nonlinear systems Algorithms that can track rapid time variation in both linear and nonlinear systems The important class of spatio-temporal systems that evolve over both space and time Many case study examples from modelling space weather, through identification of a model of the visual processing system of fruit flies, to tracking causality in EEG data are all included to demonstrate how easily the methods can be applied in practice and to show the insight that the algorithms reveal even for complex systems NARMAX algorithms provide a fundamentally different approach to nonlinear system identification and signal processing for nonlinear systems. NARMAX methods provide models that are transparent, which can easily be analysed, and which can be used to solve real problems. This book is intended for graduates, postgraduates and researchers in the sciences and engineering, and also for users from other fields who have collected data and who wish to identify models to help to understand the dynamics of their systems.

Model Predictive Control System Design and Implementation Using MATLAB®

Author : Liuping Wang
Publisher : Springer Science & Business Media
ISBN 13 : 1848823312
Total Pages : 398 pages
Book Rating : 4.8/5 (488 download)

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Book Synopsis Model Predictive Control System Design and Implementation Using MATLAB® by : Liuping Wang

Download or read book Model Predictive Control System Design and Implementation Using MATLAB® written by Liuping Wang and published by Springer Science & Business Media. This book was released on 2009-02-14 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Predictive Control System Design and Implementation Using MATLAB® proposes methods for design and implementation of MPC systems using basis functions that confer the following advantages: - continuous- and discrete-time MPC problems solved in similar design frameworks; - a parsimonious parametric representation of the control trajectory gives rise to computationally efficient algorithms and better on-line performance; and - a more general discrete-time representation of MPC design that becomes identical to the traditional approach for an appropriate choice of parameters. After the theoretical presentation, coverage is given to three industrial applications. The subject of quadratic programming, often associated with the core optimization algorithms of MPC is also introduced and explained. The technical contents of this book is mainly based on advances in MPC using state-space models and basis functions. This volume includes numerous analytical examples and problems and MATLAB® programs and exercises.

Modeling of Dynamic Systems

Author : Lennart Ljung
Publisher : Prentice Hall
ISBN 13 : 9780135970973
Total Pages : 0 pages
Book Rating : 4.9/5 (79 download)

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Book Synopsis Modeling of Dynamic Systems by : Lennart Ljung

Download or read book Modeling of Dynamic Systems written by Lennart Ljung and published by Prentice Hall. This book was released on 1994 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by a recognized authority in the field of identification and control, this book draws together into a single volume the important aspects of system identification AND physical modelling. KEY TOPICS: Explores techniques used to construct mathematical models of systems based on knowledge from physics, chemistry, biology, etc. (e.g., techniques with so called bond-graphs, as well those which use computer algebra for the modeling work). Explains system identification techniques used to infer knowledge about the behavior of dynamic systems based on observations of the various input and output signals that are available for measurement. Shows how both types of techniques need to be applied in any given practical modeling situation. Considers applications, primarily simulation. MARKET: For practicing engineers who are faced with problems of modeling.

Modeling and Analysis of Dynamic Systems

Author : Ramin S. Esfandiari
Publisher : CRC Press
ISBN 13 : 1351751646
Total Pages : 661 pages
Book Rating : 4.3/5 (517 download)

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Book Synopsis Modeling and Analysis of Dynamic Systems by : Ramin S. Esfandiari

Download or read book Modeling and Analysis of Dynamic Systems written by Ramin S. Esfandiari and published by CRC Press. This book was released on 2018-01-29 with total page 661 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling and Analysis of Dynamic Systems, Third Edition introduces MATLAB®, Simulink®, and SimscapeTM and then utilizes them to perform symbolic, graphical, numerical, and simulation tasks. Written for senior level courses/modules, the textbook meticulously covers techniques for modeling a variety of engineering systems, methods of response analysis, and introductions to mechanical vibration, and to basic control systems. These features combine to provide students with a thorough knowledge of the mathematical modeling and analysis of dynamic systems. The Third Edition now includes Case Studies, expanded coverage of system identification, and updates to the computational tools included.

PID Control System Design and Automatic Tuning using MATLAB/Simulink

Author : Liuping Wang
Publisher : John Wiley & Sons
ISBN 13 : 1119469341
Total Pages : 366 pages
Book Rating : 4.1/5 (194 download)

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Book Synopsis PID Control System Design and Automatic Tuning using MATLAB/Simulink by : Liuping Wang

Download or read book PID Control System Design and Automatic Tuning using MATLAB/Simulink written by Liuping Wang and published by John Wiley & Sons. This book was released on 2020-04-20 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers PID control systems from the very basics to the advanced topics This book covers the design, implementation and automatic tuning of PID control systems with operational constraints. It provides students, researchers, and industrial practitioners with everything they need to know about PID control systems—from classical tuning rules and model-based design to constraints, automatic tuning, cascade control, and gain scheduled control. PID Control System Design and Automatic Tuning using MATLAB/Simulink introduces PID control system structures, sensitivity analysis, PID control design, implementation with constraints, disturbance observer-based PID control, gain scheduled PID control systems, cascade PID control systems, PID control design for complex systems, automatic tuning and applications of PID control to unmanned aerial vehicles. It also presents resonant control systems relevant to many engineering applications. The implementation of PID control and resonant control highlights how to deal with operational constraints. Provides unique coverage of PID Control of unmanned aerial vehicles (UAVs), including mathematical models of multi-rotor UAVs, control strategies of UAVs, and automatic tuning of PID controllers for UAVs Provides detailed descriptions of automatic tuning of PID control systems, including relay feedback control systems, frequency response estimation, Monte-Carlo simulation studies, PID controller design using frequency domain information, and MATLAB/Simulink simulation and implementation programs for automatic tuning Includes 15 MATLAB/Simulink tutorials, in a step-by-step manner, to illustrate the design, simulation, implementation and automatic tuning of PID control systems Assists lecturers, teaching assistants, students, and other readers to learn PID control with constraints and apply the control theory to various areas. Accompanying website includes lecture slides and MATLAB/ Simulink programs PID Control System Design and Automatic Tuning using MATLAB/Simulink is intended for undergraduate electrical, chemical, mechanical, and aerospace engineering students, and will greatly benefit postgraduate students, researchers, and industrial personnel who work with control systems and their applications.

Control System Analysis and Identification with MATLAB®

Author : Anish Deb
Publisher : CRC Press
ISBN 13 : 135139956X
Total Pages : 360 pages
Book Rating : 4.3/5 (513 download)

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Book Synopsis Control System Analysis and Identification with MATLAB® by : Anish Deb

Download or read book Control System Analysis and Identification with MATLAB® written by Anish Deb and published by CRC Press. This book was released on 2018-10-09 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Key Features: The Book Covers recent results of the traditional block pulse and other functions related material Discusses ‘functions related to block pulse functions’ extensively along with their applications Contains analysis and identification of linear time-invariant systems, scaled system, and sampled-data system Presents an overview of piecewise constant orthogonal functions starting from Haar to sample-and-hold function Includes examples and MATLAB codes with supporting numerical exampless.