State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties PDF full book. Access full book title State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties by Noack, Benjamin. Download full books in PDF and EPUB format.
Author: Noack, Benjamin
Publisher: KIT Scientific Publishing
ISBN: 3731501244
Category : Technology & Engineering
Languages : en
Pages : 292
Get Book Here
Book Description
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.
Author: Noack, Benjamin
Publisher: KIT Scientific Publishing
ISBN: 3731501244
Category : Technology & Engineering
Languages : en
Pages : 292
Get Book Here
Book Description
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.
Author: Gilitschenski, Igor
Publisher: KIT Scientific Publishing
ISBN: 3731504731
Category : Electronic computers. Computer science
Languages : en
Pages : 198
Get Book Here
Book Description
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.
Author: Wolfgang Desch
Publisher: Birkhäuser
ISBN: 303488530X
Category : Mathematics
Languages : en
Pages : 403
Get Book Here
Book Description
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.
Author: Baum, Marcus
Publisher: KIT Scientific Publishing
ISBN: 3731500787
Category : Computers
Languages : en
Pages : 190
Get Book Here
Book Description
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.
Author: Fischer, Joerg
Publisher: KIT Scientific Publishing
ISBN: 3731503050
Category : Electronic computers. Computer science
Languages : en
Pages : 184
Get Book Here
Book Description
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.
Author: Faion, Florian
Publisher: KIT Scientific Publishing
ISBN: 3731505177
Category : Technology (General)
Languages : en
Pages : 229
Get Book Here
Book Description
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.
Author: Janya-anurak, Chettapong
Publisher: KIT Scientific Publishing
ISBN: 3731506424
Category : Electronic computers. Computer science
Languages : en
Pages : 248
Get Book Here
Book Description
In this work, the Uncertainty Quantification (UQ) approaches combined systematically to analyze and identify systems. The generalized Polynomial Chaos (gPC) expansion is applied to reduce the computational effort. The framework using gPC based on Bayesian UQ proposed in this work is capable of analyzing the system systematically and reducing the disagreement between the model predictions and the measurements of the real processes to fulfill user defined performance criteria.
Author: Pfaff, Florian
Publisher: KIT Scientific Publishing
ISBN: 3731509326
Category : Computers
Languages : en
Pages : 270
Get Book Here
Book Description
Author: Reinhardt, Marc
Publisher: KIT Scientific Publishing
ISBN: 3731503425
Category : Mathematics
Languages : en
Pages : 262
Get Book Here
Book Description
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.
Author: Klemm, Martin
Publisher: KIT Scientific Publishing
ISBN: 3731508001
Category : Augmented reality
Languages : en
Pages : 242
Get Book Here
Book Description
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.
