Download or read book Identification of Linear Systems written by J. Schoukens and published by Elsevier. This book was released on 2014-06-28 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concentrates on the problem of accurate modeling of linear systems. It presents a thorough description of a method of modeling a linear dynamic invariant system by its transfer function. The first two chapters provide a general introduction and review for those readers who are unfamiliar with identification theory so that they have a sufficient background knowledge for understanding the methods described later. The main body of the book looks at the basic method used by the authors to estimate the parameter of the transfer function, how it is possible to optimize the excitation signals. Further chapters extend the estimation method proposed. Applications are then discussed and the book concludes with practical guidelines which illustrate the method and offer some rules-of-thumb.

Download or read book Robust Identification of Linear Systems written by V. David Vandelinde and published by . This book was released on 1977 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first two sections of this report survey the current techniques of identification and time series analysis for linear, time invariant, single-input, single-output systems with noisy measurements. Typically, this additive noise has been modeled either as being completely specified (e.g., a Gaussian with known parameters) or as being required to satisfy general conditions such as whiteness and non-correlation with the input. Departures from the assumed noise model sometimes cause severe deterioration in the efficiency of available identification algorithms. Since it seems reasonable to have some, if not complete, knowledge of the operating environment, it is assumed in this report that the measurement noise w sub k has a distribution F(W) = (1-e)K(w) + eC(w), where K(,) is a completely specified distribution and C(.) belongs to some broad class of distribution. In the third section, a robust scheme for estimating the system cross correlations is proposed in order to desensitize the performance of the identification algorithm to the distribution of w sub k. Extensive computer simulations show that the proposal provides a robust identification technique which has good uniform behavior over a variety of distribution for w sub k. (Author).

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.

Download or read book Identification of Continuous Time Systems written by Allamaraju Subrahmanyam and published by CRC Press. This book was released on 2019-12-06 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Models of dynamical systems are required for various purposes in the field of systems and control. The models are handled either in discrete time (DT) or in continuous time (CT). Physical systems give rise to models only in CT because they are based on physical laws which are invariably in CT. In system identification, indirect methods provide DT models which are then converted into CT. Methods of directly identifying CT models are preferred to the indirect methods for various reasons. The direct methods involve a primary stage of signal processing, followed by a secondary stage of parameter estimation. In the primary stage, the measured signals are processed by a general linear dynamic operation—computational or realized through prefilters, to preserve the system parameters in their native CT form—and the literature is rich on this aspect. In this book: Identification of Continuous-Time Systems-Linear and Robust Parameter Estimation, Allamaraju Subrahmanyam and Ganti Prasada Rao consider CT system models that are linear in their unknown parameters and propose robust methods of estimation. This book complements the existing literature on the identification of CT systems by enhancing the secondary stage through linear and robust estimation. In this book, the authors provide an overview of CT system identification, consider Markov-parameter models and time-moment models as simple linear-in-parameters models for CT system identification, bring them into mainstream model parameterization via basis functions, present a methodology to robustify the recursive least squares algorithm for parameter estimation of linear regression models, suggest a simple off-line error quantification scheme to show that it is possible to quantify error even in the absence of informative priors, and indicate some directions for further research. This modest volume is intended to be a useful addition to the literature on identifying CT systems.

Download or read book New Tools for Robustness of Linear Systems written by B. Ross Barmish and published by Macmillan College. This book was released on 1994 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Robust Estimation of Crosscorrelation for Parameter Identification of Linear Systems written by Santanu Basu and published by . This book was released on 1978 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Robust Linear System Identification in Eta infty written by Hüseyin Akçay and published by . This book was released on 1992 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Robust Control and Linear Parameter Varying Approaches written by Olivier Sename and published by Springer. This book was released on 2013-02-01 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vehicles are complex systems (non-linear, multi-variable) where the abundance of embedded controllers should ensure better security. This book aims at emphasizing the interest and potential of Linear Parameter Varying methods within the framework of vehicle dynamics, e.g. proposed control-oriented model, complex enough to handle some system non linearities but still simple for control or observer design, take into account the adaptability of the vehicle's response to driving situations, to the driver request and/or to the road sollicitations, manage interactions between various actuators to optimize the dynamic behavior of vehicles. This book results from the 32th International Summer School in Automatic that held in Grenoble, France, in September 2011, where recent methods (based on robust control and LPV technics), then applied to the control of vehicle dynamics, have been presented. After some theoretical background and a view on some recent works on LPV approaches (for modelling, analysis, control, observation and diagnosis), the main emphasis is put on road vehicles but some illustrations are concerned with railway, aerospace and underwater vehicles. The main objective of the book is to demonstrate the value of this approach for controlling the dynamic behavior of vehicles. It presents, in a rm way, background and new results on LPV methods and their application to vehicle dynamics.

Download or read book Linear Systems written by Alok Sinha and published by CRC Press. This book was released on 2007-01-31 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: Balancing rigorous theory with practical applications, Linear Systems: Optimal and Robust Control explains the concepts behind linear systems, optimal control, and robust control and illustrates these concepts with concrete examples and problems. Developed as a two-course book, this self-contained text first discusses linear systems, incl

Download or read book Linear Parameter varying System Identification written by Paulo Lopes dos Santos and published by World Scientific. This book was released on 2012 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This review volume reports the state-of-the-art in Linear Parameter Varying (LPV) system identification. It focuses on the most recent LPV identification methods for both discrete-time and continuous-time models--

Download or read book Modeling and Identification of Linear Parameter Varying Systems written by Roland Toth and published by Springer. This book was released on 2010-07-11 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through the past 20 years, the framework of Linear Parameter-Varying (LPV) systems has become a promising system theoretical approach to handle the control of mildly nonlinear and especially position dependent systems which are common in mechatronic applications and in the process industry. The birth of this system class was initiated by the need of engineers to achieve better performance for nonlinear and time-varying dynamics, c- mon in many industrial applications, than what the classical framework of Linear Time-Invariant (LTI) control can provide. However, it was also a p- mary goal to preserve simplicity and “re-use” the powerful LTI results by extending them to the LPV case. The progress continued according to this philosophy and LPV control has become a well established ?eld with many promising applications. Unfortunately, modeling of LPV systems, especially based on measured data (which is called system identi?cation) has seen a limited development sincethebirthoftheframework. Currentlythisbottleneck oftheLPVfra- work is halting the transfer of the LPV theory into industrial use. Without good models that ful?ll the expectations of the users and without the und- standing how these models correspond to the dynamics of the application, it is di?cult to design high performance LPV control solutions. This book aims to bridge the gap between modeling and control by investigating the fundamental questions of LPV modeling and identi?cation. It explores the missing details of the LPV system theory that have hindered the formu- tion of a well established identi?cation framework.

Download or read book Nonlinear System Identification written by Oliver Nelles and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 785 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.

Download or read book Control and Dynamic Systems V56 Digital and Numeric Techniques and Their Application in Control Systems written by C.T. Leonides and published by Academic Press. This book was released on 2012-12-02 with total page 593 pages. Available in PDF, EPUB and Kindle. Book excerpt: Control and Dynamic Systems: Advances in Theory and Applications, Volume 56: Digital and Numeric Techniques and their Applications in Control Systems, Part 2 of 2 covers the significant developments in digital and numerical techniques for the analysis and design of modern complex control systems. This volume is composed of 12 chapters and starts with a description of the design techniques of linear constrained discrete-time control systems. The subsequent chapters describe the techniques dealing with robust real-time system identification, the adaptive control algorithms, and the utilization of methods from generalized interpolation and operator theory to deal with a wide range of problems in robust control. These topics are followed by reviews f the decentralized control design for interconnected uncertain systems; the computation of frequency response of descriptor systems by rational interpolation; the techniques for the synthesis of multivariable feedback control laws; and the effect of the initial condition in state estimation for discrete-time linear systems. Other chapters illustrate practical, efficient, and reliable numerical algorithms for robust multivariable control design of linear time-invariant systems, as well as a complete analysis of closed-loop transfer recovery in discrete-time systems using observer-based controllers. The last chapters provide the techniques in robust policy-making in the global economic environment and the implications of robust control techniques for continuous-time systems. This book will prove useful to process, control, systems, and design engineers.

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

Download or read book Robust Controllability of Linear Systems written by Valery Y. Glizer and published by Nova Science Publishers. This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book System Identification and Robust Control written by Steen Toffner-Clausen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies, ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. The present text Steen T0ffner-Clausen deals with both system identification and robust control. It provides a very comprehensive tutorial introduction to some of the most difficult topics in robust control theory before considering applications problems. Traditional Hoo robust control design concepts for multivariable systems are first considered and the problems of robust stability and performance are discussed. The following chapter introduces the idea of the structured singular value and applies this to both analysis and synthesis problems. The author manages to provide a very straightforward introduction to this subject and also introduces some new ideas.

Download or read book Control and Dynamic Systems V53 High Performance Systems Techniques and Applications written by C.T. Leonides and published by Elsevier. This book was released on 2012-12-02 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Control and Dynamic Systems: Advances in Theory and Applications, Volume 53: High Performance Systems Techniques and Applications covers the significant research works on the issues and applications of high performance control systems techniques. This book is divided into 11 chapters and starts with an examination of the contribution of computing power with advances in theory in global optimization. The next chapters present robust solution techniques for combined filtering and parameter estimation in discrete time and the design and analysis of model reference adaptive control techniques for both continuous and discrete time multivariable plants with additive and multiplicative unmodeled dynamics. These topics are followed by discussions of the decentralized adaptive control; robust recursive estimation of states and parameters of bilinear systems; the design of robust control systems under uncertainty cases; and the techniques for state estimation for linear stationary dynamic systems that are subject to unknown time varying plant and output disturbances. Other chapters deal with the sliding control algorithm, the techniques in robust broadband beamforming, and the different categories of robust robotic controllers. The final chapter looks into the problems and issues of performance and versatility of non-linear control and the application of artificial neural networks. This book is of great value to process, control, mechanical, and design engineers.