Linear Estimation in Interconnected Sensor Systems with Information Constraints

Linear Estimation in Interconnected Sensor Systems with Information Constraints
Author: Reinhardt, Marc
Publisher: KIT Scientific Publishing
Total Pages: 262
Release: 2015-04-15
Genre: Mathematics
ISBN: 3731503425

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.

Directional Estimation for Robotic Beating Heart Surgery

Directional Estimation for Robotic Beating Heart Surgery
Author: Kurz, Gerhard
Publisher: KIT Scientific Publishing
Total Pages: 272
Release: 2015-05-26
Genre: Electronic computers. Computer science
ISBN: 3731503824

In robotic beating heart surgery, a remote-controlled robot can be used to carry out the operation while automatically canceling out the heart motion. The surgeon controlling the robot is shown a stabilized view of the heart. First, we consider the use of directional statistics for estimation of the phase of the heartbeat. Second, we deal with reconstruction of a moving and deformable surface. Third, we address the question of obtaining a stabilized image of the heart.

Deterministic Sampling for Nonlinear Dynamic State Estimation

Deterministic Sampling for Nonlinear Dynamic State Estimation
Author: Gilitschenski, Igor
Publisher: KIT Scientific Publishing
Total Pages: 198
Release: 2016-04-19
Genre: Electronic computers. Computer science
ISBN: 3731504731

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.

Intraoperative Planning and Execution of Arbitrary Orthopedic Interventions Using Handheld Robotics and Augmented Reality

Intraoperative Planning and Execution of Arbitrary Orthopedic Interventions Using Handheld Robotics and Augmented Reality
Author: Klemm, Martin
Publisher: KIT Scientific Publishing
Total Pages: 242
Release: 2018-11-23
Genre: Augmented reality
ISBN: 3731508001

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.

Tracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems

Tracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems
Author: Faion, Florian
Publisher: KIT Scientific Publishing
Total Pages: 229
Release: 2016-09-13
Genre: Technology (General)
ISBN: 3731505177

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.

Tracking Extended Objects with Active Models and Negative Measurements

Tracking Extended Objects with Active Models and Negative Measurements
Author: Zea Cobo, Antonio Kleber
Publisher: KIT Scientific Publishing
Total Pages: 212
Release: 2019-04-09
Genre: Electronic computers. Computer science
ISBN: 373150877X

Extended object tracking deals with estimating the shape and pose of an object based on noisy point measurements. This task is not straightforward, as we may be faced with scarce low-quality measurements, little a priori information, or we may be unable to observe the entire target. This work aims to address these challenges by incorporating ideas from active contours and exploiting information from negative measurements, which tell us where the target cannot be.

Variance-Constrained Multi-Objective Stochastic Control and Filtering

Variance-Constrained Multi-Objective Stochastic Control and Filtering
Author: Lifeng Ma
Publisher: John Wiley & Sons
Total Pages: 422
Release: 2015-04-27
Genre: Mathematics
ISBN: 1118929462

Unifies existing and emerging concepts concerning multi-objective control and stochastic control with engineering-oriented phenomena Establishes a unified theoretical framework for control and filtering problems for a class of discrete-time nonlinear stochastic systems with consideration to performance Includes case studies of several nonlinear stochastic systems Investigates the phenomena of incomplete information, including missing/degraded measurements, actuator failures and sensor saturations Considers both time-invariant systems and time-varying systems Exploits newly developed techniques to handle the emerging mathematical and computational challenges

State Estimation and Stabilization of Nonlinear Systems

State Estimation and Stabilization of Nonlinear Systems
Author: Abdellatif Ben Makhlouf
Publisher: Springer Nature
Total Pages: 439
Release: 2023-11-06
Genre: Technology & Engineering
ISBN: 3031379705

This book presents the separation principle which is also known as the principle of separation of estimation and control and states that, under certain assumptions, the problem of designing an optimal feedback controller for a stochastic system can be solved by designing an optimal observer for the system's state, which feeds into an optimal deterministic controller for the system. Thus, the problem may be divided into two halves, which simplifies its design. In the context of deterministic linear systems, the first instance of this principle is that if a stable observer and stable state feedback are built for a linear time-invariant system (LTI system hereafter), then the combined observer and feedback are stable. The separation principle does not true for nonlinear systems in general. Another instance of the separation principle occurs in the context of linear stochastic systems, namely that an optimum state feedback controller intended to minimize a quadratic cost is optimal for the stochastic control problem with output measurements. The ideal solution consists of a Kalman filter and a linear-quadratic regulator when both process and observation noise are Gaussian. The term for this is linear-quadratic-Gaussian control. More generally, given acceptable conditions and when the noise is a martingale (with potential leaps), a separation principle, also known as the separation principle in stochastic control, applies when the noise is a martingale (with possible jumps).

Robust Integration of Model-Based Fault Estimation and Fault-Tolerant Control

Robust Integration of Model-Based Fault Estimation and Fault-Tolerant Control
Author: Jianglin Lan
Publisher: Springer Nature
Total Pages: 275
Release: 2020-12-11
Genre: Technology & Engineering
ISBN: 3030587606

Robust Integration of Model-Based Fault Estimation and Fault-Tolerant Control is a systematic examination of methods used to overcome the inevitable system uncertainties arising when a fault estimation (FE) function and a fault-tolerant controller interact as they are employed together to compensate for system faults and maintain robustly acceptable system performance. It covers the important subject of robust integration of FE and FTC with the aim of guaranteeing closed-loop stability. The reader’s understanding of the theory is supported by the extensive use of tutorial examples, including some MATLAB®-based material available from the Springer website and by industrial-applications-based material. The text is structured into three parts: Part I examines the basic concepts of FE and FTC, providing extensive insight into the importance of and challenges involved in their integration; Part II describes five effective strategies for the integration of FE and FTC: sequential, iterative, simultaneous, adaptive-decoupling, and robust decoupling; and Part III begins to extend the proposed strategies to nonlinear and large-scale systems and covers their application in the fields of renewable energy, robotics and networked systems. The strategies presented are applicable to a broad range of control problems, because in the absence of faults the FE-based FTC naturally reverts to conventional observer-based control. The book is a useful resource for researchers and engineers working in the area of fault-tolerant control systems, and supplementary material for a graduate- or postgraduate-level course on fault diagnosis and FTC. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.