Download or read book An Optimal Parameter Discretization Strategy for Multiple Model Adaptive Estimation and Control written by Stuart N. Sheldon and published by . This book was released on 1989 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: A method is proposed for designing multiple model adaptive estimators (MMAE) to provide combined state and parameter estimation in the presence of an uncertain parameter vector. It is assumed that the parameter varies over a continuous region and a finite number of constant-gain filters is available for the estimation. The estimator elemental filters are chosen by minimizing a cost functional representing the average state prediction error autocorrelation, with the average taken as the true parameter ranges over the admissible parameter set. A second-order example is used to illustrate the increase in performance over previously accepted filter selection methods. By minimizing a cost functional representing the average parameter prediction error autocorrelation, a parameter estimator is designed which is different from the state estimator. The parameter estimator found with this method provides lower average mean square parameter estimation error than previously accepted design methods. An analogous method is proposed for designing multiple model adaptive controllers to provide stabilizing control in the presence of an uncertain parameter vector. A finite number of constant-gain controllers is used to regulate a system with a parameter vector that varies over a continuous region of the parameter space. The controller elemental filters are chosen by minimizing a cost functional representing the average regulation error autocorrelation, with the average taken as the true parameter ranges over the admissible parameter set. Keywords: Numerical optimization, Adaptive control systems, Theses. (aw).
Download or read book New Algorithms for Moving Bank Multiple Model Adaptive Estimation written by Juan R. Vasquez and published by . This book was released on 1998-05-01 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: The focus of this research is to provide methods for generating precise parameter estimates in the face of potentially significant parameter variations such as system component failures. The standard Multiple Model Adaptive Estimation (MMAE) algorithm uses a bank of Kalman filters, each based on a different model of the system. A new moving-bank MMAE algorithm is developed based on exploitation of the density data available from the MMAE. The methods used to exploit this information include various measures of the density data and a decision-making logic used to move, expand, and contract the MMAE bank of filters. Parameter discretization within the MMAE refers to selection of the parameter values assumed by the elemental Kalman filters. A new parameter discretization method is developed based on the probabilities associated with the generalized Chi-Squared random variables formed by residual information from the elemental Kalman filters within the MMAE. Modifications to an existing discretization method are also presented, permitting application of this method in real time and to nonlinear system models or linear/linearized models that are unstable or astable. These new algorithms are validated through computer simulation of an aircraft navigation system subjected to interference/jamming while attempting a successful precision landing of the aircraft.
Download or read book American Doctoral Dissertations written by and published by . This book was released on 1999 with total page 848 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Adaptive Estimation and Control written by Keigo Watanabe and published by . This book was released on 1991 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unifies the partitioned adaptive estimators for stochastic systems and applies them to other estimation and control problems. The techniques, not restricted to lumped-parameter systems with unknown constant parameters, serve as a starting point for more complicated problems.
Download or read book Adaptive Estimation and Parameter Identification Using Multiple Model Estimation Algorithm written by Michael Athans and published by . This book was released on 1976 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this report is to introduce an adaptive estimation and parameter identification scheme which the authors call Multiple Model Estimation Algorithm (MMEA). The MMEA consists of a bank of Kalman filters with each matched to a possible parameter vector. The state estimates generated by these Kalman filters are then combined using a weighted sum with the a posteriori hypothesis probabilities as weighting factors. If one of the selected parameter vectors coincides with the true parameter vector, this algorithm gives the minimum variance state and parameter estimates. Algorithms for filtering, smoothing, and prediction are derived for linear and nonlinear systems. They are described in a tutorial fashion with results stated explicitly so that they can be readily used for computer implementation. Approaches for the extension of MMEA to a more general class of adaptive estimation problems are outlined. Several further research topics are also suggested.
Download or read book Dissertation Abstracts International written by and published by . This book was released on 2002 with total page 858 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Error Control Adaptive Discretizations and Applications Part 1 written by and published by Elsevier. This book was released on 2024-06-29 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Error Control, Adaptive Discretizations, and Applications, Volume 58, Part One highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. Chapters in this release cover hp adaptive Discontinuous Galerkin strategies driven by a posteriori error estimation with application to aeronautical flow problems, An anisotropic mesh adaptation method based on gradient recovery and optimal shape elements, and Model reduction techniques for parametrized nonlinear partial differential equations. - Covers multi-scale modeling - Includes updates on data-driven modeling - Presents the latest information on large deformations of multi-scale materials
Download or read book Government Reports Announcements Index written by and published by . This book was released on 1990-03 with total page 1188 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Space Station Systems written by and published by . This book was released on 1986 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optimal Adaptive Estimation Structure and Parameter Adaptation Part I Linear Models written by D. G. Lainiotis and published by . This book was released on 1969 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Bayesian approach to optimal adatpive estimation with continuous as well as discrete data is presented. Both structure and parameter adaptation are considered and specific recursive adaptation algorithms are derived for gaussian process models and linear dynamics. Specifically, for the class of adaptive estimation problems with linear dynamic models and gaussian excitations, a form of the 'partition' theorem is given that is applicable both for structure and parameter adaptation. The 'partition' or 'decomposition' theorem effects the partition of the essentially nonlinear estimation problem into two parts, a linear non-adaptive part consisting of ordinary Kalman estimators and a nonlinear part that incorporates the adaptive or learning nature of the adaptive estimator. In addition, simple performance measures are introduced for the on-line performance evaluation of the adaptive estimator. The on-line performance measure utilize quantities available from the adaptive estimator and hence a minimum of additional computational effort is required for evaluation. Adaptive estimators are given for filtering, prediction, as well as smoothing. (Author).
Download or read book Model Based Parameter Estimation written by Hans Georg Bock and published by Springer Science & Business Media. This book was released on 2013-02-26 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This judicious selection of articles combines mathematical and numerical methods to apply parameter estimation and optimum experimental design in a range of contexts. These include fields as diverse as biology, medicine, chemistry, environmental physics, image processing and computer vision. The material chosen was presented at a multidisciplinary workshop on parameter estimation held in 2009 in Heidelberg. The contributions show how indispensable efficient methods of applied mathematics and computer-based modeling can be to enhancing the quality of interdisciplinary research. The use of scientific computing to model, simulate, and optimize complex processes has become a standard methodology in many scientific fields, as well as in industry. Demonstrating that the use of state-of-the-art optimization techniques in a number of research areas has much potential for improvement, this book provides advanced numerical methods and the very latest results for the applications under consideration.
Download or read book Lectures on Adaptive Parameter Estimation written by C. Richard Johnson and published by Prentice Hall. This book was released on 1988 with total page 216 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 1990 with total page 996 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Generalized Residual Multiple Model Adaptive Estimation of Parameters and States written by Charles D. Ormsby and published by . This book was released on 2003-10 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation develops a modification to the standard Multiple Model Adaptive Estimator (MMAE) which allows the use of a new "generalized residual" in the hypothesis conditional probability calculation. The generalized residual is a linear combination of traditional Kalman filter residuals and "post-fit" Kalman filter residuals which are calculated after measurement incorporation. This modified MMAE is termed a Generalized Residual Multiple Model Adaptive Estimator (GRMMAE). The dissertation provides a derivation of the hypothesis conditional probability formula which the GRMMAE uses to calculate probabilities that each elemental filter in the GRMMAE contains the correct parameter value. Through appropriate choice of a single scalar GRMMAE design parameter, the GRMMAE can be designed to be equivalent to a traditional MMAE, a post-fit residual modified MMAE, or any number of yet unused MMAEs. The original GRMMAE design goal was to choose the GRMMAE design parameter that caused the fastest GRMMAE convergence to the correct hypothesis. However, this dissertation demonstrates that the GRMMAE design parameter can lead to beta-dominance, a negative performance effect in the GRMMAE. This is a key contribution of this research as other researchers have previously suggested that the use of post-fit residuals may be advantageous in certain MMAE applications. This dissertation directly addresses the use of post-fit residuals by those researchers and demonstrates that, for their application, equivalent performance is achieved using a traditional MMAE. (10 tables, 27 figures, 47 refs.)
Download or read book Modified Multiple Model Adaptive Estimation M3AE for Simultaneous Parameter and State Estimation written by Mikel Mark Miller and published by . This book was released on 1998-03-01 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many estimation problems, it is desired to estimate system states and parameters simultaneously. However, inherent to traditional estimation architectures of the past, the designer has had to make a trade-off decision between designs intended for accurate state estimation versus designs concerned with accurate parameter estimation. This research develops one solution to this trade-off decision by proposing a new architecture based on Kalman filtering (KF) and Multiple Model Adaptive Estimation (MMAE) techniques. This new architecture, the Modified-MMAE (M3AE), exploits the benefits of an MMAE designed for accurate parameter estimation, and yet performs at least as well in state estimation as an MMAE designed for accurate state estimation. The M3AE accomplishes the simultaneous estimation task by providing accurate state estimates from a single KF designed to accept accurate parameter estimates from the MMAE. Additionally, an M3AE approximate covariance analysis capability is developed, giving the designer a valuable design tool for analyzing and predicting M3AE performance before actually implementing the M3AE and conducting a time-consuming full-scale Monte Carlo performance analysis. Finally, the M3AE architecture is applied to two existing research examples to demonstrate the performance improvement over that of conventional MMAEs. The first example involves a simple second-order mechanical translational system, in which the system's natural frequency is the uncertain parameter. The second example involves a 13-state nonlinear integrated Global Positioning System/Inertial Navigation System (GPS/INS) system, in which the variance of the measurement noise affecting the GPS outputs, is the uncertain parameter.
Download or read book Trends in PDE Constrained Optimization written by Günter Leugering and published by Springer. This book was released on 2014-12-22 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization problems subject to constraints governed by partial differential equations (PDEs) are among the most challenging problems in the context of industrial, economical and medical applications. Almost the entire range of problems in this field of research was studied and further explored as part of the Deutsche Forschungsgemeinschaft (DFG) priority program 1253 on “Optimization with Partial Differential Equations” from 2006 to 2013. The investigations were motivated by the fascinating potential applications and challenging mathematical problems that arise in the field of PDE constrained optimization. New analytic and algorithmic paradigms have been developed, implemented and validated in the context of real-world applications. In this special volume, contributions from more than fifteen German universities combine the results of this interdisciplinary program with a focus on applied mathematics. The book is divided into five sections on “Constrained Optimization, Identification and Control”, “Shape and Topology Optimization”, “Adaptivity and Model Reduction”, “Discretization: Concepts and Analysis” and “Applications”. Peer-reviewed research articles present the most recent results in the field of PDE constrained optimization and control problems. Informative survey articles give an overview of topics that set sustainable trends for future research. This makes this special volume interesting not only for mathematicians, but also for engineers and for natural and medical scientists working on processes that can be modeled by PDEs.
Download or read book Government Reports Annual Index written by and published by . This book was released on 1990 with total page 1576 pages. Available in PDF, EPUB and Kindle. Book excerpt:
