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Author : P. Eykhoff
Publisher : Chichester ; New York : Wiley
ISBN 13 :
Total Pages : 584 pages
Book Rating : 4.3/5 (97 download)
Download or read book System Identification Parameter and State Estimation written by P. Eykhoff and published by Chichester ; New York : Wiley. This book was released on 1974-05-23 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Pieter Eykhoff
Publisher :
ISBN 13 : 9780783795058
Total Pages : 555 pages
Book Rating : 4.7/5 (95 download)
Download or read book System Identification written by Pieter Eykhoff and published by . This book was released on 1974-01-01 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Paul Van Den Hof
Publisher : Elsevier
ISBN 13 : 9780080437095
Total Pages : 2080 pages
Book Rating : 4.4/5 (37 download)
Download or read book System Identification (SYSID '03) written by Paul Van Den Hof and published by Elsevier. This book was released on 2004-06-29 with total page 2080 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scope of the symposium covers all major aspects of system identification, experimental modelling, signal processing and adaptive control, ranging from theoretical, methodological and scientific developments to a large variety of (engineering) application areas. It is the intention of the organizers to promote SYSID 2003 as a meeting place where scientists and engineers from several research communities can meet to discuss issues related to these areas. Relevant topics for the symposium program include: Identification of linear and multivariable systems, identification of nonlinear systems, including neural networks, identification of hybrid and distributed systems, Identification for control, experimental modelling in process control, vibration and modal analysis, model validation, monitoring and fault detection, signal processing and communication, parameter estimation and inverse modelling, statistical analysis and uncertainty bounding, adaptive control and data-based controller tuning, learning, data mining and Bayesian approaches, sequential Monte Carlo methods, including particle filtering, applications in process control systems, motion control systems, robotics, aerospace systems, bioengineering and medical systems, physical measurement systems, automotive systems, econometrics, transportation and communication systems *Provides the latest research on System Identification *Contains contributions written by experts in the field *Part of the IFAC Proceedings Series which provides a comprehensive overview of the major topics in control engineering.
Author : Rolf Isermann
Publisher : Springer
ISBN 13 : 9783540871552
Total Pages : 705 pages
Book Rating : 4.8/5 (715 download)
Download or read book Identification of Dynamic Systems written by Rolf Isermann and published by Springer. This book was released on 2011-04-08 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.
Author : Tien-Li Chia
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (256 download)
Download or read book Parameter Identification and State Estimation of Constrained Systems (recursive, Projection) written by Tien-Li Chia and published by . This book was released on 1986 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : R. Isermann
Publisher : Elsevier
ISBN 13 : 148313945X
Total Pages : 93 pages
Book Rating : 4.4/5 (831 download)
Download or read book System Identification written by R. Isermann and published by Elsevier. This book was released on 2014-05-23 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: System Identification is a special section of the International Federation of Automatic Control (IFAC)-Journal Automatica that contains tutorial papers regarding the basic methods and procedures utilized for system identification. Topics include modeling and identification; step response and frequency response methods; correlation methods; least squares parameter estimation; and maximum likelihood and prediction error methods. After analyzing the basic ideas concerning the parameter estimation methods, the book elaborates on the asymptotic properties of these methods, and then investigates the application of the methods to particular model structures. The text then discusses the practical aspects of process identification, which includes the usual, general procedures for process identification; selection of input signals and sampling time; offline and on-line identification; comparison of parameter estimation methods; data filtering; model order testing; and model verification. Computer program packages are also discussed. This compilation of tutorial papers aims to introduce the newcomers and non-specialists in this field to some of the basic methods and procedures used for system identification.
Author : Tien-Li Chia
Publisher :
ISBN 13 :
Total Pages : 260 pages
Book Rating : 4.:/5 (125 download)
Download or read book Parameter Identification and State Estimation of Constained Systems written by Tien-Li Chia and published by . This book was released on 1985 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Samandeep Singh Dhaliwal
Publisher :
ISBN 13 :
Total Pages : 166 pages
Book Rating : 4.:/5 (769 download)
Download or read book State Estimation and Parameter Identification of Continuous-time Nonlinear Systems written by Samandeep Singh Dhaliwal and published by . This book was released on 2011 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of parameter and state estimation of a class of nonlinear systems is addressed. An adaptive identifier and observer are used to estimate the parameters and the state variables simultaneously. The proposed method is derived using a new formulation. Uncertainty sets are defined for the parameters and a set of auxiliary variables for the state variables. An algorithm is developed to update these sets using the available information. The algorithm proposed guarantees the convergence of parameters and the state variables to their true value. In addition to its application in difficult estimation problems, the algorithm has also been adapted to handle fault detection problems. The technique of estimation is applied to two broad classes of systems. The first involves a class of continuous time nonlinear systems subject to bounded unknown exogenous disturbance with constant parameters. Using the proposed set-based adaptive estimation, the parameters are updated only when an improvement in the precision of the parameter estimates can be guaranteed. The formulation provides robustness to parameter estimation error and bounded disturbance. The parameter uncertainty set and the uncertainty associated with an auxiliary variable is updated such that the set is guaranteed to contain the unknown true values. The second class of system considered is a class of nonlinear systems with timevarying parameters. Using a generalization of the set-based adaptive estimation technique proposed, the estimates of the parameters and state are updated to guarantee convergence to a neighborhood of their true value. The algorithm proposed can also be extended to detect the fault in the system, injected by drastic change in the time-varying parameter values. To study the practical applicability of the developed method, the estimation of state variables and time-varying parameters of salt in a stirred tank process has been performed. The results of the experimental application demonstrate the ability of the proposed techniques to estimate the state variables and time-varying parameters of an uncertain practical system.
Author : Robert Haber
Publisher : Springer Science & Business Media
ISBN 13 : 9780792358572
Total Pages : 428 pages
Book Rating : 4.3/5 (585 download)
Download or read book Nonlinear system identification. 2. Nonlinear system structure identification written by Robert Haber and published by Springer Science & Business Media. This book was released on 1999 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the second part of a two-volume handbook presenting a comprehensive overview of nonlinear dynamic system identification. The books include many aspects of nonlinear processes such as modelling, parameter estimation, structure search, nonlinearity and model validity tests.
Author : Lennart Ljung
Publisher : Prentice Hall
ISBN 13 :
Total Pages : 552 pages
Book Rating : 4.3/5 (91 download)
Download or read book System Identification written by Lennart Ljung and published by Prentice Hall. This book was released on 1987 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: System and models. Methods. User's choice. Some concepts from probability theory. Some statistical techniques for linear regressions.
Author : Naim Logic
Publisher :
ISBN 13 : 9783838332352
Total Pages : 156 pages
Book Rating : 4.3/5 (323 download)
Download or read book Power System State Estimation written by Naim Logic and published by . This book was released on 2010-01 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Michael Allan Budin
Publisher :
ISBN 13 :
Total Pages : 94 pages
Book Rating : 4.F/5 ( download)
Download or read book Parameter Identification and State Estimation for Linear Systems written by Michael Allan Budin and published by . This book was released on 1969 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Karel J. Keesman
Publisher : Springer Science & Business Media
ISBN 13 : 0857295225
Total Pages : 334 pages
Book Rating : 4.8/5 (572 download)
Download or read book System Identification written by Karel J. Keesman and published by Springer Science & Business Media. This book was released on 2011-05-16 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: System Identification shows the student reader how to approach the system identification problem in a systematic fashion. The process is divided into three basic steps: experimental design and data collection; model structure selection and parameter estimation; and model validation, each of which is the subject of one or more parts of the text. Following an introduction on system theory, particularly in relation to model representation and model properties, the book contains four parts covering: • data-based identification – non-parametric methods for use when prior system knowledge is very limited; • time-invariant identification for systems with constant parameters; • time-varying systems identification, primarily with recursive estimation techniques; and • model validation methods. A fifth part, composed of appendices, covers the various aspects of the underlying mathematics needed to begin using the text. The book uses essentially semi-physical or gray-box modeling methods although data-based, transfer-function system descriptions are also introduced. The approach is problem-based rather than rigorously mathematical. The use of finite input–output data is demonstrated for frequency- and time-domain identification in static, dynamic, linear, nonlinear, time-invariant and time-varying systems. Simple examples are used to show readers how to perform and emulate the identification steps involved in various control design methods with more complex illustrations derived from real physical, chemical and biological applications being used to demonstrate the practical applicability of the methods described. End-of-chapter exercises (for which a downloadable instructors’ Solutions Manual is available from fill in URL here) will both help students to assimilate what they have learned and make the book suitable for self-tuition by practitioners looking to brush up on modern techniques. Graduate and final-year undergraduate students will find this text to be a practical and realistic course in system identification that can be used for assessing the processes of a variety of engineering disciplines. System Identification will help academic instructors teaching control-related to give their students a good understanding of identification methods that can be used in the real world without the encumbrance of undue mathematical detail.
Author : A. Smith
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781979800747
Total Pages : 182 pages
Book Rating : 4.8/5 (7 download)
Download or read book System Identification With Matlab written by A. Smith and published by Createspace Independent Publishing Platform. This book was released on 2017-11-20 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Online estimation algorithms estimate the parameters and states of a model when new data is available during the operation of the physical system. The System Identification Toolbox software uses linear, extended, and unscented Kalman filter, or particle filter algorithms for online state estimation. The toolbox uses recursive prediction error minimization algorithms for online parameter estimation. Consider a heating and cooling system that does not have prior information about the environment in which it operates. Suppose that this system must heat or cool a room to achieve a certain temperature in a given amount of time. To fulfill its objective, the system must obtain knowledge of the temperature and insulation characteristics of the room. You can estimate the insulation characteristics of the room while the system is online (operational). For this estimation, use the system effort as the input and the room temperature as the output. You can use the estimated model to improve system behavior. Online estimation is ideal for estimating small deviations in the parameter values of a system at a known operating point. Common applications of online estimation include: - Adaptive control - Estimate a plant model to modify the controller based on changes in the plant model. - Fault detection - Compare the online plant model with the idealized or reference plant model to detect a fault (anomaly) in the plant. - Soft sensing - Generate a "measurement" based on the estimated plant model, and use this measurement for feedback control or fault detection. - Verification of the experiment-data quality before starting offline estimation - Before using the measured data for offline estimation, perform online estimation for a few iterations. The online estimation provides a quick check of whether the experiment used excitation signals that captured the relevant system dynamics. Online parameter estimation is typically performed using a recursive algorithm. To estimate the parameter values at a time step, recursive algorithms use the current measurements and previous parameter estimates. Therefore, recursive algorithms are efficient in terms of memory usage. Also, recursive algorithms have smaller computational demands. This efficiency makes them suited to online and embedded applications. In System Identification Toolbox you can perform online parameter estimation in Simulink or at the command line: - In Simulink, use the Recursive Least Squares Estimator and Recursive Polynomial Model Estimator blocks to perform online parameter estimation. You can also estimate a state-space model online from these models by using the Recursive Polynomial Model Estimator and Model Type Converter blocks together. You can generate C/C++ code and Structured Text for these blocks using Simulink Coder and Simulink PLC Coder softwares. - At the command line, use recursiveAR, recursiveARMA, recursiveARX, recursiveARMAX, recursiveOE, recursiveBJ, and recursiveLS commands to estimate model parameters for your model structure. Unlike estimation in Simulink, you can change the properties of the recursive estimation algorithm during online estimation. You can generate code and standalone applications using MATLAB Coder and MATLAB Compiler software. When you perform online parameter estimation in Simulink or at the command line, the following requirements apply: - Model must be discrete-time linear or nearly linear with parameters that vary slowly with time. - Structure of the estimated model must be fixed during estimation. - iddata object is not supported during online parameter estimation. Specify estimation output data as a real scalar and input data as a real scalar or vector. Online estimation algorithms estimate the parameters of a model when new data is available during the operation of the model. In offline estimation, you first collect all the input/output data and then estimate the model parameters .
Author : A. Y. Allidina
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (643 download)
Download or read book System Identification and Parameter Estimation written by A. Y. Allidina and published by . This book was released on 1978 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ali Abur
Publisher : CRC Press
ISBN 13 : 9780203913673
Total Pages : 350 pages
Book Rating : 4.9/5 (136 download)
Download or read book Power System State Estimation written by Ali Abur and published by CRC Press. This book was released on 2004-03-24 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering an up-to-date account of the strategies utilized in state estimation of electric power systems, this text provides a broad overview of power system operation and the role of state estimation in overall energy management. It uses an abundance of examples, models, tables, and guidelines to clearly examine new aspects of state estimation, the testing of network observability, and methods to assure computational efficiency. Includes numerous tutorial examples that fully analyze problems posed by the inclusion of current measurements in existing state estimators and illustrate practical solutions to these challenges. Written by two expert researchers in the field, Power System State Estimation extensively details topics never before covered in depth in any other text, including novel robust state estimation methods, estimation of parameter and topology errors, and the use of ampere measurements for state estimation. It introduces various methods and computational issues involved in the formulation and implementation of the weighted least squares (WLS) approach, presents statistical tests for the detection and identification of bad data in system measurements, and reveals alternative topological and numerical formulations for the network observability problem.
Author : Ferdinand van der Heijden
Publisher : John Wiley & Sons
ISBN 13 : 0470090146
Total Pages : 440 pages
Book Rating : 4.4/5 (7 download)
Download or read book Classification, Parameter Estimation and State Estimation written by Ferdinand van der Heijden and published by John Wiley & Sons. This book was released on 2005-06-10 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Classification, Parameter Estimation and State Estimation is a practical guide for data analysts and designers of measurement systems and postgraduates students that are interested in advanced measurement systems using MATLAB. 'Prtools' is a powerful MATLAB toolbox for pattern recognition and is written and owned by one of the co-authors, B. Duin of the Delft University of Technology. After an introductory chapter, the book provides the theoretical construction for classification, estimation and state estimation. The book also deals with the skills required to bring the theoretical concepts to practical systems, and how to evaluate these systems. Together with the many examples in the chapters, the book is accompanied by a MATLAB toolbox for pattern recognition and classification. The appendix provides the necessary documentation for this toolbox as well as an overview of the most useful functions from these toolboxes. With its integrated and unified approach to classification, parameter estimation and state estimation, this book is a suitable practical supplement in existing university courses in pattern classification, optimal estimation and data analysis. Covers all contemporary main methods for classification and estimation. Integrated approach to classification, parameter estimation and state estimation Highlights the practical deployment of theoretical issues. Provides a concise and practical approach supported by MATLAB toolbox. Offers exercises at the end of each chapter and numerous worked out examples. PRtools toolbox (MATLAB) and code of worked out examples available from the internet Many examples showing implementations in MATLAB Enables students to practice their skills using a MATLAB environment
