Non-linear state estimation for integrating adaptronic joints in parallel robots

In dieser Arbeit wird die nichtlineare Zustandsschätzung bei mechatronischen Systemen am Beispiel von Parallelrobotern beschrieben. Das Hauptziel ist, die Reibkräfte und -momente in den Gelenken des Roboters zu detektieren und diese für regelungstechnische Zwecke zur Verfügung zu stellen. Das entwickelte Verfahren zur Beobachtung erlaubt die Bestimmung veränderlicher Reibmomente in den Gelenken unter Einbeziehung des vollständigen Robotermodells. Ein besonderer Fokus liegt dabei auf der Nutzbarkeit der Informationen zur Steuerung adaptronischer Gelenke, so dass sich das hier entwickelte Verfahren von adaptiven Ansätzen abhebt. Die Herleitung der Methoden nutzt die besondere Struktur der Modelle mechatronischer Systeme aus. Ein Schwerpunkt liegt auf der genauen Untersuchung der Beobachtbarkeit der gesuchten Reibmomente des Systems und die sich daraus ergebenden Bedingungen beim Entwurf. Das vorgestellte Verfahren basiert auf der Transformation des Systems und nutzt die Methoden der Differentialgeometrie zur Analyse nichtlinearer Systeme aus. Der hier entwickelte Ansatz unterscheidet sich von denen der klassischen Form zur Beobachterentwicklung und bietet systemunabhängig eine globale Konvergenz in den geschätzten Größen. Die erzielte Fehlerdynamik ist dabei linear. Die Schließung des Regelkreises über die geschätzten Zustände wird untersucht, um die zur Stabilität notwendigen Bedingungen an die Entwurfsparameter zu definieren. Die theoretischen Ergebnisse sind in Simulation und am Versuchsträger verifiziert. Dazu wurde die Schätzung der Parameter an einem Parallelroboter mit zwei Freiheitsgraden durchgeführt. Das Verfahren wurde nachträglich in die bestehende Steuerungsstruktur integriert und zur Schätzung der Parameter verwendet. Dazu wurden die bereits vorhandenen Messwerte benutzt, zusätzliche Sensoren wurden nicht in das System eingebracht.This thesis presents a method for non-linear state estimation in parallel kinematic machines. These machines serve as an example for a more general class of mechatronical systems that are described by similar equations. The main objective of this work is to detect the varying torques and forces that are induced by friction within joints. This state information is supposed to be fed back into the control system in order to maintain the performance of the controller. Furthermore, the information gained by the observer has to be utilizable as input for the control of adaptronic joints. The potential use of the state information as the control variable in closed control loops is the major difference to adaptive concepts. The derivation of the observer exploits the special structure of the dynamic equations of mechatronic systems. Methods from differential geometry are applicable to the differential equations and allow the transformation to more convenient descriptions of the nonlinear system. The observability of the system is analyzed in detail. Consequently, conditions for non-linear observer design are derived. The concept presented here differs from the classical non-linear observer and allows the estimation of friction without further restrictions to the systems parameters, while achieving global convergence. The error dynamics are described by linear differential equations. Stability of closed loop control using the estimated states is analyzed and necessary conditions are derived. Afterwards, the theoretical results are verified in simulation and on a real system. The observer was implemented and integrated in an existing control setup of a two dimensional parallel robot. Without installing additional sensors the derived observer provides the targeted states

Defining Natural History: Assessment of the Ability of College Students to Aid in Characterizing Clinical Progression of Niemann-Pick Disease, Type C

Niemann-Pick Disease, type C (NPC) is a fatal, neurodegenerative, lysosomal storage disorder. It is a rare disease with broad phenotypic spectrum and variable age of onset. These issues make it difficult to develop a universally accepted clinical outcome measure to assess urgently needed therapies. To this end, clinical investigators have defined emerging, disease severity scales. The average time from initial symptom to diagnosis is approximately 4 years. Further, some patients may not travel to specialized clinical centers even after diagnosis. We were therefore interested in investigating whether appropriately trained, community-based assessment of patient records could assist in defining disease progression using clinical severity scores. In this study we evolved a secure, step wise process to show that pre-existing medical records may be correctly assessed by non-clinical practitioners trained to quantify disease progression. Sixty-four undergraduate students at the University of Notre Dame were expertly trained in clinical disease assessment and recognition of major and minor symptoms of NPC. Seven clinical records, randomly selected from a total of thirty seven used to establish a leading clinical severity scale, were correctly assessed to show expected characteristics of linear disease progression. Student assessment of two new records donated by NPC families to our study also revealed linear progression of disease, but both showed accelerated disease progression, relative to the current severity scale, especially at the later stages. Together, these data suggest that college students may be trained in assessment of patient records, and thus provide insight into the natural history of a disease

Investigating Ammonium By-product Removal for Ureolytic Bio-cementation Using Meter-scale Experiments.

Microbially Induced Calcite Precipitation (MICP), or bio-cementation, is a promising bio-mediated technology that can improve the engineering properties of soils through the precipitation of calcium carbonate. Despite significant advances in the technology, concerns regarding the fate of produced NH4+ by-products have remained largely unaddressed. In this study, five 3.7-meter long soil columns each containing one of three different soils were improved using ureolytic bio-cementation, and post-treatment NH4+ by-product removal was investigated during the application of 525 L of a high pH and high ionic strength rinse solution. During rinsing, reductions in aqueous NH4+ were observed in all columns from initial concentrations between ≈100 mM to 500 mM to final values between ≈0.3 mM and 20 mM with higher NH4+ concentrations observed at distances furthest from the injection well. In addition, soil Vs measurements completed during rinse injections suggested that no significant changes in cementation integrity occurred during NH4+ removal. After rinsing and a 12 hour stop flow period, all column solutions achieved cumulative NH4+ removals exceeding 97.9%. Soil samples collected following rinsing, however, contained significant sorbed NH4+ masses that appeared to have a near linear relationship with surrounding aqueous NH4+ concentrations. While these results suggest that NH4+ can be successfully removed from bio-cemented soils, acceptable limits for NH4+ aqueous concentrations and sorbed NH4+ masses will likely be governed by site-specific requirements and may require further investigation and refinement of the developed techniques

Characterization of Crystallographic Structures Using Bragg-Edge Neutron Imaging at the Spallation Neutron Source

Over the past decade, wavelength-dependent neutron radiography, also known as Bragg-edge imaging, has been employed as a non-destructive bulk characterization method due to its sensitivity to coherent elastic neutron scattering that is associated with crystalline structures. Several analysis approaches have been developed to quantitatively determine crystalline orientation, lattice strain, and phase distribution. In this study, we report a systematic investigation of the crystal structures of metallic materials (such as selected textureless powder samples and additively manufactured (AM) Inconel 718 samples), using Bragg-edge imaging at the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source (SNS). Firstly, we have implemented a phenomenological Gaussian-based fitting in a Python-based computer called iBeatles. Secondly, we have developed a model-based approach to analyze Bragg-edge transmission spectra, which allows quantitative determination of the crystallographic attributes. Moreover, neutron diffraction measurements were carried out to validate the Bragg-edge analytical methods. These results demonstrate that the microstructural complexity (in this case, texture) plays a key role in determining the crystallographic parameters (lattice constant or interplanar spacing), which implies that the Bragg-edge image analysis methods must be carefully selected based on the material structures