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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 : 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 : Michael Allan Budin
Publisher :
ISBN 13 :
Total Pages : 79 pages
Book Rating : 4.:/5 (18 download)
Download or read book Parameter Indentification and State Estimation for Linear Systems written by Michael Allan Budin and published by . This book was released on 1970 with total page 79 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 : 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 : Hebertt Sira-Ramírez
Publisher : John Wiley & Sons
ISBN 13 : 1118730585
Total Pages : 498 pages
Book Rating : 4.1/5 (187 download)
Download or read book Algebraic Identification and Estimation Methods in Feedback Control Systems written by Hebertt Sira-Ramírez and published by John Wiley & Sons. This book was released on 2014-03-13 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algebraic Identification and Estimation Methods in Feedback Control Systems presents a model-based algebraic approach to online parameter and state estimation in uncertain dynamic feedback control systems. This approach evades the mathematical intricacies of the traditional stochastic approach, proposing a direct model-based scheme with several easy-to-implement computational advantages. The approach can be used with continuous and discrete, linear and nonlinear, mono-variable and multi-variable systems. The estimators based on this approach are not of asymptotic nature, and do not require any statistical knowledge of the corrupting noises to achieve good performance in a noisy environment. These estimators are fast, robust to structured perturbations, and easy to combine with classical or sophisticated control laws. This book uses module theory, differential algebra, and operational calculus in an easy-to-understand manner and also details how to apply these in the context of feedback control systems. A wide variety of examples, including mechanical systems, power converters, electric motors, and chaotic systems, are also included to illustrate the algebraic methodology. Key features: Presents a radically new approach to online parameter and state estimation. Enables the reader to master the use and understand the consequences of the highly theoretical differential algebraic viewpoint in control systems theory. Includes examples in a variety of physical applications with experimental results. Covers the latest developments and applications. Algebraic Identification and Estimation Methods in Feedback Control Systems is a comprehensive reference for researchers and practitioners working in the area of automatic control, and is also a useful source of information for graduate and undergraduate students.
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 : Daniel Sigalov
Publisher :
ISBN 13 :
Total Pages : 130 pages
Book Rating : 4.:/5 (951 download)
Download or read book State Estimation in Linear Systems with Random Parameters written by Daniel Sigalov and published by . This book was released on 2015 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Yiran Hu
Publisher :
ISBN 13 :
Total Pages : 205 pages
Book Rating : 4.:/5 (682 download)
Download or read book Identification and State Estimation for Linear Parameter Varying Systems with Application to Battery Management System Design written by Yiran Hu and published by . This book was released on 2010 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: The tools developed for LPV systems are then applied to solve the problems of model identification and state of charge (SoC) estimation for battery cells. The model identification problem is tackled using both identification schemes so that differences in performance and effectiveness between the methods can be compared and contrasted. A SoC estimator based on LPV system state estimation techniques is then designed using the model identified. Because parametric uncertainty is inherent in the estimator designed, the stability and performance of the estimator is analyzed using the notion of input to state stability. Experimental data is then used to illustrate the efficacy of this method. The goal of these applications is to show the relevance of the LPV structure and techniques to problems in battery management system design, so that research will be done to solve other problems in this area under the same framework.
Author : G. A. Bekey
Publisher : Elsevier
ISBN 13 : 1483165787
Total Pages : 869 pages
Book Rating : 4.4/5 (831 download)
Download or read book Identification and System Parameter Estimation 1982 written by G. A. Bekey and published by Elsevier. This book was released on 2016-06-06 with total page 869 pages. Available in PDF, EPUB and Kindle. Book excerpt: Identification and System Parameter Estimation 1982 covers the proceedings of the Sixth International Federation of Automatic Control (IFAC) Symposium. The book also serves as a tribute to Dr. Naum S. Rajbman. The text covers issues concerning identification and estimation, such as increasing interrelationships between identification/estimation and other aspects of system theory, including control theory, signal processing, experimental design, numerical mathematics, pattern recognition, and information theory. The book also provides coverage regarding the application and problems faced by several engineering and scientific fields that use identification and estimation, such as biological systems, traffic control, geophysics, aeronautics, robotics, economics, and power systems. Researchers from all scientific fields will find this book a great reference material, since it presents topics that concern various disciplines.
Author : Manoj Krishna Venkatesan
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (135 download)
Download or read book Finite Time Joint Parameter and State Estimation Using Python written by Manoj Krishna Venkatesan and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Parameter and state estimation of linear systems play a significant role in the realm of control systems. More often than not, the parameters and the state values are not readily available and must be deduced from the applied input and the measured output information. Algebraic estimators have been introduced to combat the parameter identification problem, under the major assumption that an accurate measurement of the output signal is available. If the measured output is not noise-free, estimating the output states and their derivatives is not possible. This thesis focuses on the algebraic estimation and filtering of the parameters and the states of linear systems using a forward-backward kernel representation of differential invariants of a system, that will be able to handle measured output signals with high noise values. The kernels, working in tandem with the Kalman filter and Raunch-Tung-Striebel (RTS) smoother, provide accurate parameters and state values even for high noise levels in the measured output. Further, this thesis explains in detail, the construction of a python based estimation library that modularises the algorithms used for state and parameter estimation. This would facilitate applications like implementing model based controllers, and also help in further analysis of a system. This library provides a flexible infrastructure to test the performance of different algorithms against the benchmark results from the Unscented Kalman Filter(UKF). It is a collaborative effort to drive the research forward for further advancements and handling more complex non-homogeneous and non-linear systems"--
Author : Michael Allan Budin
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (7 download)
Download or read book Parameter Identification and State Estimation written by Michael Allan Budin and published by . This book was released on 1972 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Teymuraz Eliazov
Publisher :
ISBN 13 :
Total Pages : 190 pages
Book Rating : 4.:/5 (179 download)
Download or read book Simultaneous State and Parameter Estimation in Linear Systems written by Teymuraz Eliazov and published by . This book was released on 1987 with total page 190 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 : Peter van Overschee
Publisher : Springer Science & Business Media
ISBN 13 : 1461304652
Total Pages : 263 pages
Book Rating : 4.4/5 (613 download)
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.
Author : Lennart Ljung
Publisher : Pearson Education
ISBN 13 : 0132440539
Total Pages : 873 pages
Book Rating : 4.1/5 (324 download)
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 873 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.
Author : Diego Mincarelli
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (88 download)
Download or read book Parameters and State Estimation for Switched Systems written by Diego Mincarelli and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hybrid systems have been widely studied in the literature and became a powerful tool for modeling systems coming from many engineering fields. A common definition of hybrid systems is a combination of both continuous-time and discrete event systems. Examples of hybrid systems include networks, multi-agent systems, mechanical devices, robot path planning, biological systems. Researches on hybrid systems cover all fields of control theory such as stability analysis, control and observation problems or supervision. In the context of switched systems, which is a particular class of hybrid systems, this thesis aims at studying the problem related to extracting information about the system parameters and the state from the knowledge of the output.This study is motivated by various purposes: modeling, monitoring, fault detection and identification for the systems safety, output feedback control. For those reasons,the identification and the observation are at the core of decision and control problems.The first part of the thesis is devoted to extend the applicability of the algebra-based methods for on-line constant parameter estimation, developed by INRIA - Non-A project-team, to the case of systems with piecewise constant parameters. To this end, a procedure for the estimation of the parameters and the switching times is developed in the framework of switched systems.Such an approach enables a simultaneous algebraic estimation of both parameters and change time instants. The novelty and efficiency of the proposed identification algorithms mainly lie in their non asymptotic nature. The second part of the thesis addresses the problem of observer design for estimating the discrete and the continuous state of switched systems.Since switched systems contain a family of continuous-time systems and discrete-event systems, the evolution of their dynamics is naturally non-smooth, and this increases the difficulties to solve the observation problem. For instance, the estimates have to be provided before the next switch takes place. Thus, we propose an observer based on finite-time techniques (sliding-mode based) for the reconstruction of the continuous states and the switching signal (discrete state) in finite-time. Finally, we deal with another class of switched systems where the parameters, in each subsystem, are time-varying. For this kind of models, called switched linear parameter varying systems, we design an estimator for reconstructing the discrete state, by using parameter identification techniques.
