Download or read book Nonlinear State and Parameter Estimation of Spatially Distributed Systems written by Felix Sawo and published by Karlsruher Institut Fur Technologie. This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis two probabilistic model-based estimators are introduced that allow the reconstruction and identification of space-time continuous physical systems. The Sliced Gaussian Mixture Filter (SGMF) exploits linear substructures in mixed linear/nonlinear systems, and thus is well-suited for identifying various model parameters. The Covariance Bounds Filter (CBF) allows the efficient estimation of widely distributed systems in a decentralized fashion.
Download or read book Topics in Identification and Distributed Parameter Systems written by Erhard Bühler and published by Springer-Verlag. This book was released on 2013-07-02 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Spatio Temporal Modeling of Nonlinear Distributed Parameter Systems written by Han-Xiong Li and published by Springer Science & Business Media. This book was released on 2011-02-24 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein systems and their identifi cation methods. Then, the traditional Volterra model is extended to DPS, which results in the spatio-temporal Volterra model and its identification algorithm. All these methods are based on linear time/space separation. Sometimes, the nonlinear time/space separation can play a better role in modeling of very complex processes. Thus, a nonlinear time/space separation based neural modeling is also presented for a class of DPS with more complicated dynamics. Finally, all these modeling approaches are successfully applied to industrial thermal processes, including a catalytic rod, a packed-bed reactor and a snap curing oven. The work is presented giving a unifi ed view from time/space separation. The book also illustrates applications to thermal processes in the electronics packaging and chemical industry. This volume assumes a basic knowledge about distributed parameter systems, system modeling and identifi cation. It is intended for researchers, graduate students and engineers interested in distributed parameter systems, nonlinear systems, and process modeling and control.
Download or read book State Estimation for Distributed Systems with Stochastic and Set membership Uncertainties written by Noack, Benjamin and published by KIT Scientific Publishing. This book was released on 2014-01-02 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: State estimation techniques for centralized, distributed, and decentralized systems are studied. An easy-to-implement state estimation concept is introduced that generalizes and combines basic principles of Kalman filter theory and ellipsoidal calculus. By means of this method, stochastic and set-membership uncertainties can be taken into consideration simultaneously. Different solutions for implementing these estimation algorithms in distributed networked systems are presented.
Download or read book Deterministic Sampling for Nonlinear Dynamic State Estimation written by Gilitschenski, Igor and published by KIT Scientific Publishing. This book was released on 2016-04-19 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this work is improving existing and suggesting novel filtering algorithms for nonlinear dynamic state estimation. Nonlinearity is considered in two ways: First, propagation is improved by proposing novel methods for approximating continuous probability distributions by discrete distributions defined on the same continuous domain. Second, nonlinear underlying domains are considered by proposing novel filters that inherently take the underlying geometry of these domains into account.
Download or read book Control and Estimation of Distributed Parameter Systems Nonlinear Phenomena written by Wolfgang Desch and published by Birkhäuser. This book was released on 2012-12-06 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: 22 papers on control of nonlinear partial differential equations highlight the area from a broad variety of viewpoints. They comprise theoretical considerations such as optimality conditions, relaxation, or stabilizability theorems, as well as the development and evaluation of new algorithms. A significant part of the volume is devoted to applications in engineering, continuum mechanics and population biology.
Download or read book Parameter Estimation Problems for Distributed Systems Using a Multigrid Method written by and published by . This book was released on 1986 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data driven Simulations of Distributed Systems written by David Alonso Barajas-Solano and published by . This book was released on 2013 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation deals with mathematical modeling of complex distributed systems whose parameters are heterogeneous and heavily under-specified by data. Such problems are ubiquitous in every field of science and engineering, where one or more deterministic models exist to describe a given phenomenon but only a limited number of measurements of a model's parameters and its state variables are available. The main focus of this dissertation is on parameter identification (PI) and uncertainty quantification (UQ). The first part of this dissertation deals with development and numerical implementation of an algorithm to compute accurately and efficiently Green's functions, which are often used in both PI and UQ analyses of linear systems with piece-wise continuous parameters. The second part of this dissertation explores the propagation of parametric uncertainty through a modeling process, in which quantities of interest are described by nonlinear elliptic and parabolic partial differential equations. We demonstrate that the variance of uncertain parameters (a measure of their uncertainty) strongly affects the regularity of a system's stochastic response, restricting the use of modern probabilistic UQ methods (e.g, polynomial chaos expansions and stochastic collocation methods) to low distributed parameters with low noise-to-signal ratios. High ratios adversely affect the stability and scalability of such methods. The third part of this dissertation deals with this issue by developing a multi-level Monte Carlo algorithm that outperforms direct Monte Carlo and allows for systematic treatment of different sources of bias in the computed estimators. In the final part of this dissertation we explore two PI strategies based on a Bayesian framework. The first strategy is to sample a posterior distribution using a generalized hybrid Monte Carlo (gHMC) method. We develop acceleration schemes for improving the efficiency of gHMC, and use them to estimate parameters in reactive transport systems with sparse concentration measurements. The second strategy is to compute the maximum a posteriori estimator of the configuration of spatially distributed, piece-wise continuous parameters by using a linearized functional minimization algorithm. Total variation regularization (TV) is employed as a prior on the parameter distribution, which allows one to capture large-scale features of system behavior from sparse measurements of both system parameters and transient system states.
Download or read book Distributed Parameter Control Systems written by Spyros G. Tzafestas and published by Elsevier. This book was released on 2013-10-22 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: Distributed Parameter Control Systems: Theory and Application is a two-part book consisting of 10 theoretical and five application-oriented chapters contributed by well-known workers in the distributed-parameter systems. The book covers topics of distributed parameter control systems in the areas of simulation, identification, state estimation, stability, control (optimal, stochastic, and coordinated), numerical approximation methods, optimal sensor, and actuator positioning. Five applications works include chemical reactors, heat exchangers, petroleum reservoirs/aquifers, and nuclear reactors. The text will be a useful reference for both graduate students and professional researchers working in the field.
Download or read book Simultaneous Tracking and Shape Estimation of Extended Objects written by Baum, Marcus and published by KIT Scientific Publishing. This book was released on 2014-07-30 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work is concerned with the simultaneous tracking and shape estimation of a mobile extended object based on noisy sensor measurements. Novel methods are developed for coping with the following two main challenges: i) The computational complexity due to the nonlinearity and high-dimensionality of the problem, and ii) the lack of statistical knowledge about possible measurement sources on the extended object.
Download or read book Linear Estimation in Interconnected Sensor Systems with Information Constraints written by Reinhardt, Marc and published by KIT Scientific Publishing. This book was released on 2015-04-15 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: A ubiquitous challenge in many technical applications is to estimate an unknown state by means of data that stems from several, often heterogeneous sensor sources. In this book, information is interpreted stochastically, and techniques for the distributed processing of data are derived that minimize the error of estimates about the unknown state. Methods for the reconstruction of dependencies are proposed and novel approaches for the distributed processing of noisy data are developed.
Download or read book Parameter Estimation Problems for Distributed Systems Using a Multigrid Method written by Shlomo Ta'asan and published by . This book was released on 1986 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optimal Sequence Based Control of Networked Linear Systems written by Fischer, Joerg and published by KIT Scientific Publishing. This book was released on 2015-01-12 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Networked Control Systems (NCS), components of a control loop are connected by data networks that may introduce time-varying delays and packet losses into the system, which can severly degrade control performance. Hence, this book presents the newly developed S-LQG (Sequence-Based Linear Quadratic Gaussian) controller that combines the sequence-based control method with the well-known LQG approach to stochastic optimal control in order to compensate for the network-induced effects.
Download or read book Intraoperative Planning and Execution of Arbitrary Orthopedic Interventions Using Handheld Robotics and Augmented Reality written by Klemm, Martin and published by KIT Scientific Publishing. This book was released on 2018-11-23 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: The focus of this work is a generic, intraoperative and image-free planning and execution application for arbitrary orthopedic interventions using a novel handheld robotic device and optical see-through glasses (AR). This medical CAD application enables the surgeon to intraoperatively plan the intervention directly on the patient's bone. The glasses and all the other instruments are accurately calibrated using new techniques. Several interventions show the effectiveness of this approach.
Download or read book Multitarget Tracking Using Orientation Estimation for Optical Belt Sorting written by Pfaff, Florian and published by KIT Scientific Publishing. This book was released on 2019-10-31 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optimal Measurement Methods for Distributed Parameter System Identification written by Dariusz Ucinski and published by CRC Press. This book was released on 2019-08-30 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: For dynamic distributed systems modeled by partial differential equations, existing methods of sensor location in parameter estimation experiments are either limited to one-dimensional spatial domains or require large investments in software systems. With the expense of scanning and moving sensors, optimal placement presents a critical problem. Optimal Measurement Methods for Distributed Parameter System Identification discusses the characteristic features of the sensor placement problem, analyzes classical and recent approaches, and proposes a wide range of original solutions, culminating in the most comprehensive and timely treatment of the issue available. By presenting a step-by-step guide to theoretical aspects and to practical design methods, this book provides a sound understanding of sensor location techniques. Both researchers and practitioners will find the case studies, the proposed algorithms, and the numerical examples to be invaluable. This text also offers results that translate easily to MATLAB and to Maple. Assuming only a basic familiarity with partial differential equations, vector spaces, and probability and statistics, and avoiding too many technicalities, this is a superb resource for researchers and practitioners in the fields of applied mathematics, electrical, civil, geotechnical, mechanical, chemical, and environmental engineering.
Download or read book Tracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems written by Faion, Florian and published by KIT Scientific Publishing. This book was released on 2016-09-13 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: We discuss theory and application of extended object tracking. This task is challenging as sensor noise prevents a correct association of the measurements to their sources on the object, the shape itself might be unknown a priori, and due to occlusion effects, only parts of the object are visible at a given time. We propose an approach to track the parameters of arbitrary objects, which provides new solutions to the above challenges, and marks a significant advance to the state of the art.
