Download or read book Decomposition Algorithms for On line Estimation with Nonlinear Models written by Joao S. Albuquerque and published by . This book was released on 1994 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "Dynamic state and parameter estimation for nonlinear systems usually leads to large nonlinear problems when the governing differential constraints are discretized under a simultaneous solution strategy. In this paper we discretize the set of ODEs using an Implicit Runge-Kutta integration method, and use the SQP method to solve the resulting NLP. The optimality conditions for each data set at the QP subproblem level are decoupled using an affine transform, so that the first order conditions in the state and input variables can be solved recursively and expressed as functions of the optimality conditions in the parameters, thus reducing the size of the problem and turning the effort of solving it linear with the number of data sets. As seen in our example, this approach is therefore over two orders of magnitude faster than general purpose NLP solvers."
Download or read book Decomposition Algorithms for On line Estimation with Nonlinear DAE Models written by Joao S. Albuquerque and published by . This book was released on 1995 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Estimation of Parameters from Incomplete Data for Nonlinear Models with Applications to Compartmental Models written by Mary Francis Fitzpatrick and published by . This book was released on 1992 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nonlinear Programming written by Lorenz T. Biegler and published by SIAM. This book was released on 2010-10-14 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive treatment of nonlinear programming concepts and algorithms, especially as they apply to challenging applications in chemical process engineering.
Download or read book Model Reduction of Parametrized Systems written by Peter Benner and published by Springer. This book was released on 2017-09-05 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: The special volume offers a global guide to new concepts and approaches concerning the following topics: reduced basis methods, proper orthogonal decomposition, proper generalized decomposition, approximation theory related to model reduction, learning theory and compressed sensing, stochastic and high-dimensional problems, system-theoretic methods, nonlinear model reduction, reduction of coupled problems/multiphysics, optimization and optimal control, state estimation and control, reduced order models and domain decomposition methods, Krylov-subspace and interpolatory methods, and applications to real industrial and complex problems. The book represents the state of the art in the development of reduced order methods. It contains contributions from internationally respected experts, guaranteeing a wide range of expertise and topics. Further, it reflects an important effor t, carried out over the last 12 years, to build a growing research community in this field. Though not a textbook, some of the chapters can be used as reference materials or lecture notes for classes and tutorials (doctoral schools, master classes).
Download or read book Instrument Engineers Handbook Volume 3 written by Bela G. Liptak and published by CRC Press. This book was released on 2018-10-08 with total page 1140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Instrument Engineers' Handbook – Volume 3: Process Software and Digital Networks, Fourth Edition is the latest addition to an enduring collection that industrial automation (AT) professionals often refer to as the "bible." First published in 1970, the entire handbook is approximately 5,000 pages, designed as standalone volumes that cover the measurement (Volume 1), control (Volume 2), and software (Volume 3) aspects of automation. This fourth edition of the third volume provides an in-depth, state-of-the-art review of control software packages used in plant optimization, control, maintenance, and safety. Each updated volume of this renowned reference requires about ten years to prepare, so revised installments have been issued every decade, taking into account the numerous developments that occur from one publication to the next. Assessing the rapid evolution of automation and optimization in control systems used in all types of industrial plants, this book details the wired/wireless communications and software used. This includes the ever-increasing number of applications for intelligent instruments, enhanced networks, Internet use, virtual private networks, and integration of control systems with the main networks used by management, all of which operate in a linked global environment. Topics covered include: Advances in new displays, which help operators to more quickly assess and respond to plant conditions Software and networks that help monitor, control, and optimize industrial processes, to determine the efficiency, energy consumption, and profitability of operations Strategies to counteract changes in market conditions and energy and raw material costs Techniques to fortify the safety of plant operations and the security of digital communications systems This volume explores why the holistic approach to integrating process and enterprise networks is convenient and efficient, despite associated problems involving cyber and local network security, energy conservation, and other issues. It shows how firewalls must separate the business (IT) and the operation (automation technology, or AT) domains to guarantee the safe function of all industrial plants. This book illustrates how these concerns must be addressed using effective technical solutions and proper management policies and practices. Reinforcing the fact that all industrial control systems are, in general, critically interdependent, this handbook provides a wide range of software application examples from industries including: automotive, mining, renewable energy, steel, dairy, pharmaceutical, mineral processing, oil, gas, electric power, utility, and nuclear power.
Download or read book System Identification written by Torsten Söderström and published by . This book was released on 1989 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook designed for senior undergraduate and graduate level classroom courses on system identification. Examples and problems. Annotation copyrighted by Book News, Inc., Portland, OR
Download or read book Applications of Linear and Nonlinear Models written by Erik Grafarend and published by Springer Science & Business Media. This book was released on 2012-08-15 with total page 1026 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear regression models within the first 8 chapters. Our point of view is both an algebraic view as well as a stochastic one. For example, there is an equivalent lemma between a best, linear uniformly unbiased estimation (BLUUE) in a Gauss-Markov model and a least squares solution (LESS) in a system of linear equations. While BLUUE is a stochastic regression model, LESS is an algebraic solution. In the first six chapters we concentrate on underdetermined and overdeterimined linear systems as well as systems with a datum defect. We review estimators/algebraic solutions of type MINOLESS, BLIMBE, BLUMBE, BLUUE, BIQUE, BLE, BIQUE and Total Least Squares. The highlight is the simultaneous determination of the first moment and the second central moment of a probability distribution in an inhomogeneous multilinear estimation by the so called E-D correspondence as well as its Bayes design. In addition, we discuss continuous networks versus discrete networks, use of Grassmann-Pluecker coordinates, criterion matrices of type Taylor-Karman as well as FUZZY sets. Chapter seven is a speciality in the treatment of an overdetermined system of nonlinear equations on curved manifolds. The von Mises-Fisher distribution is characteristic for circular or (hyper) spherical data. Our last chapter eight is devoted to probabilistic regression, the special Gauss-Markov model with random effects leading to estimators of type BLIP and VIP including Bayesian estimation. A great part of the work is presented in four Appendices. Appendix A is a treatment, of tensor algebra, namely linear algebra, matrix algebra and multilinear algebra. Appendix B is devoted to sampling distributions and their use in terms of confidence intervals and confidence regions. Appendix C reviews the elementary notions of statistics, namely random events and stochastic processes. Appendix D introduces the basics of Groebner basis algebra, its careful definition, the Buchberger Algorithm, especially the C. F. Gauss combinatorial algorithm.
Download or read book Process Systems Engineering 2003 written by Bingzhen Chen and published by Elsevier. This book was released on 2003-06-06 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains proceedings from the 8th International Symposium on Process Systems Engineering (PSE), which brought together the global community of process systems engineering researchers and practitioners involved in the creation and application of computing based methodologies for planning, design, operation, control, and maintenance of chemical processes. Contains proceeding from the 8th International Symposium on Process Systems EngineeringConference theme for PSE 2003 is 'supporting business decision making'
Download or read book Nonlinear Estimation written by Shovan Bhaumik and published by CRC Press. This book was released on 2019-07-24 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Estimation: Methods and Applications with Deterministic Sample Points focusses on a comprehensive treatment of deterministic sample point filters (also called Gaussian filters) and their variants for nonlinear estimation problems, for which no closed-form solution is available in general. Gaussian filters are becoming popular with the designers due to their ease of implementation and real time execution even on inexpensive or legacy hardware. The main purpose of the book is to educate the reader about a variety of available nonlinear estimation methods so that the reader can choose the right method for a real life problem, adapt or modify it where necessary and implement it. The book can also serve as a core graduate text for a course on state estimation. The book starts from the basic conceptual solution of a nonlinear estimation problem and provides an in depth coverage of (i) various Gaussian filters such as the unscented Kalman filter, cubature and quadrature based filters, Gauss-Hermite filter and their variants and (ii) Gaussian sum filter, in both discrete and continuous-discrete domain. Further, a brief description of filters for randomly delayed measurement and two case-studies are also included. Features: The book covers all the important Gaussian filters, including filters with randomly delayed measurements. Numerical simulation examples with detailed matlab code are provided for most algorithms so that beginners can verify their understanding. Two real world case studies are included: (i) underwater passive target tracking, (ii) ballistic target tracking. The style of writing is suitable for engineers and scientists. The material of the book is presented with the emphasis on key ideas, underlying assumptions, algorithms, and properties. The book combines rigorous mathematical treatment with matlab code, algorithm listings, flow charts and detailed case studies to deepen understanding.
Download or read book Journal of Chemical Engineering of Japan written by and published by . This book was released on 2005 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Includes abstracts of Kagaku kōgaku, v. 31-
Download or read book Nonlinear Control Systems Design 1992 written by M. Fliess and published by Elsevier. This book was released on 2016-07-07 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume represents most aspects of the rich and growing field of nonlinear control. These proceedings contain 78 papers, including six plenary lectures, striking a balance between theory and applications. Subjects covered include feedback stabilization, nonlinear and adaptive control of electromechanical systems, nonholonomic systems. Generalized state space systems, algebraic computing in nonlinear systems theory, decoupling, linearization and model-matching and robust control are also covered.
Download or read book New Recursive Parameter Estimation Algorithms in Impulsive Noise Environment with Application to Frequency Estimation and System Identification written by Wing-Yi Lau and published by . This book was released on 2017-01-27 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "New Recursive Parameter Estimation Algorithms in Impulsive Noise Environment With Application to Frequency Estimation and System Identification" by Wing-yi, Lau, 劉穎兒, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of the Thesis Entitled New Recursive Parameter Estimation Algorithms in Impulsive Noise Environment with Application to Frequency Estimation and System Identification submitted by Wing-Yi LAU for the degree of Master of Philosophy at The University of Hong Kong in August 2006 Least-squares (LS) parameter estimation algorithms are very useful in applications such as frequency estimation and system identification. In order to support online applications with a much lower arithmetic complexity, new QR-decomposition-(QRD)-based recursive algorithms for estimating the frequency components of multiple sinusoids based on the linear prediction (LP) approach and identifying the system under colored noise are proposed in this study. Furthermore, since the LS-based algorithms are sensitive to impulsive noise, new QRD- based recursive algorithms with M-estimation are introduced so that the robustness of the proposed algorithms can be improved and the impulsive noise can be de-emphasized and removed effectively. Simulation results show that the proposed algorithms give better performance with lower arithmetic complexity than the conventional LS algorithms. Besides parameter estimation, this thesis presents a new Kalman filter-based power spectral density (PSD) estimation algorithm for nonstationary pressure signals. The pressure signals are modeled as an autoregressive (AR) process and a stochastically perturbed difference equation constraint model is used to describe the dynamics of the AR coefficients. The proposed algorithm uses variable numbers of measurements to estimate the coefficients instead of fixed number of measurements in the conventional Kalman filter. In addition, the number of the measurements of the proposed algorithm is adaptively chosen by the intersection of confidence intervals (ICI) rule. Simulation results show that the proposed algorithm achieves a better time-frequency resolution and better tracking performance than the conventional Kalman filter-based algorithm which only updates the fixed number of measurements for each estimation. The above algorithms are proposed for linear models. For nonlinear models, this thesis proposes a new recursive parameter estimation algorithm for the nonlinear adaptive function coefficients autoregressive (AFAR) models. The AFAR model is a generalization of the familiar linear AR model and it is suitable for modeling nonlinear correlation of a time series governed by unknown nonlinearities. The nonlinearities are estimated using local polynomial regression (LPR), which gives a better bias-variance tradeoff than traditional polynomial approximations. Experimental results show that the model parameters can be estimated accurately using the proposed method. Moreover, using the close relationship between a simplified AFAR model and the nonlinear Wiener system, a new recursive algorithm for identifying the nonlinear Wiener system is proposed. Another new recursive algorithm for identifying the nonlinear Wiener-Hammerstein system (WHS) model is also proposed using the relationship between the AFAR model and the WHS model. DOI: 10.5353/th_b3759586 Subjects: Signal processing - Statistical methods Parameter estimation Algorithms
Download or read book Proceedings of the American Control Conference written by and published by . This book was released on 1994 with total page 1236 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Filtering None Linear State Space Models Methods and Economic Applications written by Kai Ming Lee and published by Rozenberg Publishers. This book was released on 2010 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Adaptive Modelling Estimation and Fusion from Data written by Chris Harris and published by Springer Science & Business Media. This book was released on 2012-10-05 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together for the first time the complete theory of data based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data based modelling new concepts including extended additive and multiplicative submodels are developed. All of these algorithms are illustrated with benchmark examples to demonstrate their efficiency. The book aims at researchers and advanced professionals in time series modelling, empirical data modelling, knowledge discovery, data mining and data fusion.
