Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov���s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications.

Algorithms for spacecraft formation flying navigation based on wireless positioning system measurements

Spacecraft formation flying navigation continues to receive a great deal of interest. The research presented in this dissertation focuses on developing methods for estimating spacecraft absolute and relative positions, assuming measurements of only relative positions using wireless sensors. The implementation of the extended Kalman filter to the spacecraft formation navigation problem results in high estimation errors and instabilities in state estimation at times. This is due tp the high nonlinearities in the system dynamic model. Several approaches are attempted in this dissertation aiming at increasing the estimation stability and improving the estimation accuracy. A differential geometric filter is implemented for spacecraft positions estimation. The differential geometric filter avoids the linearization step (which is always carried out in the extended Kalman filter) through a mathematical transformation that converts the nonlinear system into a linear system. A linear estimator is designed in the linear domain, and then transformed back to the physical domain. This approach demonstrated better estimation stability for spacecraft formation positions estimation, as detailed in this dissertation. The constrained Kalman filter is also implemented for spacecraft formation flying absolute positions estimation. The orbital motion of a spacecraft is characterized by two range extrema (perigee and apogee). At the extremum, the rate of change of a spacecraft���s range vanishes. This motion constraint can be used to improve the position estimation accuracy. The application of the constrained Kalman filter at only two points in the orbit causes filter instability. Two variables are introduced into the constrained Kalman filter to maintain the stability and improve the estimation accuracy. An extended Kalman filter is implemented as a benchmark for comparison with the constrained Kalman filter. Simulation results show that the constrained Kalman filter provides better estimation accuracy as compared with the extended Kalman filter. A Weighted Measurement Fusion Kalman Filter (WMFKF) is proposed in this dissertation. In wireless localizing sensors, a measurement error is proportional to the distance of the signal travels and sensor noise. In this proposed Weighted Measurement Fusion Kalman Filter, the signal traveling time delay is not modeled; however, each measurement is weighted based on the measured signal travel distance. The obtained estimation performance is compared to the standard Kalman filter in two scenarios. The first scenario assumes using a wireless local positioning system in a GPS denied environment. The second scenario assumes the availability of both the wireless local positioning system and GPS measurements. The simulation results show that the WMFKF has similar accuracy performance as the standard Kalman Filter (KF) in the GPS denied environment. However, the WMFKF maintains the position estimation error within its expected error boundary when the WLPS detection range limit is above 30km. In addition, the WMFKF has a better accuracy and stability performance when GPS is available. Also, the computational cost analysis shows that the WMFKF has less computational cost than the standard KF, and the WMFKF has higher ellipsoid error probable percentage than the standard Measurement Fusion method. A method to determine the relative attitudes between three spacecraft is developed. The method requires four direction measurements between the three spacecraft. The simulation results and covariance analysis show that the method���s error falls within a three sigma boundary without exhibiting any singularity issues. A study of the accuracy of the proposed method with respect to the shape of the spacecraft formation is also presented.

Time-variable gravity signal in Greenland revealed by high-low satellite-to-satellite tracking

[1] In the event of a termination of the Gravity Recovery and Climate Experiment (GRACE) mission before the launch of GRACE Follow-On (due for launch in 2017), high-low satellite-to-satellite tracking (hl-SST) will be the only dedicated observing system with global coverage available to measure the time-variable gravity field (TVG) on a monthly or even shorter time scale. Until recently, hl-SST TVG observations were of poor quality and hardly improved the performance of Satellite Laser Ranging observations. To date, they have been of only very limited usefulness to geophysical or environmental investigations. In this paper, we apply a thorough reprocessing strategy and a dedicated Kalman filter to Challenging Minisatellite Payload (CHAMP) data to demonstrate that it is possible to derive the very long-wavelength TVG features down to spatial scales of approximately 2000 km at the annual frequency and for multi-year trends. The results are validated against GRACE data and surface height changes from long-term GPS ground stations in Greenland. We find that the quality of the CHAMP solutions is sufficient to derive long-term trends and annual amplitudes of mass change over Greenland. We conclude that hl-SST is a viable source of information for TVG and can serve to some extent to bridge a possible gap between the end-of-life of GRACE and the availability of GRACE Follow-On.

Differential dynamic properties of scleroderma fibroblasts in response to perturbation of environmental stimuli.

Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

Differential dynamic properties of scleroderma fibroblasts in response to perturbation of environmental stimuli.

Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

Fine-grained indoor positioning and tracking systems

Indoor positioning has attracted considerable attention for decades due to the increasing demands for location based services. In the past years, although numerous methods have been proposed for indoor positioning, it is still challenging to find a convincing solution that combines high positioning accuracy and ease of deployment. Radio-based indoor positioning has emerged as a dominant method due to its ubiquitousness, especially for WiFi. RSSI (Received Signal Strength Indicator) has been investigated in the area of indoor positioning for decades. However, it is prone to multipath propagation and hence fingerprinting has become the most commonly used method for indoor positioning using RSSI. The drawback of fingerprinting is that it requires intensive labour efforts to calibrate the radio map prior to experiments, which makes the deployment of the positioning system very time consuming. Using time information as another way for radio-based indoor positioning is challenged by time synchronization among anchor nodes and timestamp accuracy. Besides radio-based positioning methods, intensive research has been conducted to make use of inertial sensors for indoor tracking due to the fast developments of smartphones. However, these methods are normally prone to accumulative errors and might not be available for some applications, such as passive positioning. This thesis focuses on network-based indoor positioning and tracking systems, mainly for passive positioning, which does not require the participation of targets in the positioning process. To achieve high positioning accuracy, we work on some information of radio signals from physical-layer processing, such as timestamps and channel information. The contributions in this thesis can be divided into two parts: time-based positioning and channel information based positioning. First, for time-based indoor positioning (especially for narrow-band signals), we address challenges for compensating synchronization offsets among anchor nodes, designing timestamps with high resolution, and developing accurate positioning methods. Second, we work on range-based positioning methods with channel information to passively locate and track WiFi targets. Targeting less efforts for deployment, we work on range-based methods, which require much less calibration efforts than fingerprinting. By designing some novel enhanced methods for both ranging and positioning (including trilateration for stationary targets and particle filter for mobile targets), we are able to locate WiFi targets with high accuracy solely relying on radio signals and our proposed enhanced particle filter significantly outperforms the other commonly used range-based positioning algorithms, e.g., a traditional particle filter, extended Kalman filter and trilateration algorithms. In addition to using radio signals for passive positioning, we propose a second enhanced particle filter for active positioning to fuse inertial sensor and channel information to track indoor targets, which achieves higher tracking accuracy than tracking methods solely relying on either radio signals or inertial sensors.

Persistently elevated troponin I in heart failure patients - a suitable prognosticator and a possible boon to public health?

Baseline elevation of troponin I (TnI) has been associated with worse outcomes in heart failure (HF). However, the prevalence of persistent TnI elevation and its association with clinical outcomes has not been well described. HF is a major public health issue due to its wide prevalence and prognosticators of this condition will have a significant impact on public health. Methods: A retrospective study was performed in 510 patients with an initial HF admission between 2002 to 2004, and all subsequent hospital admissions up to May 2009 were recorded in a de-identified database. Persistent TnI elevation was defined as a level ���0.05 ng/ml on ���3 HF admissions. Baseline characteristics, hospital readmissions and all cause mortality were compared between patients with persistent TnI elevation (Persistent), patients with no persistence of TnI (Nonpersistent) and patients who had less than three hospital admissions (admission <3) groups. Also the same data was analyzed using the mean method in which the mean value of all recorded troponin values of each patient was used to define persistence i.e. patients who had a mean troponin level ���0.05 ng/ml were classified as persistent. Results: Mean age of our cohort was 68.4 years out of which 99.6% subjects were male, 62.4% had ischemic HF. 78.2% had NYHA class III to IV HF, mean LVEF was 25.9%. Persistent elevation of TnI was seen in 26% of the cohort and in 66% of patients with more than 3 hospital admissions. Mean TnI level was 0.67 �� 0.15 ng/ml in the 'Persistent' group. Mean TnI using the mean method was 1.11 �� 7.25 ng/ml. LVEF was significantly lower in persistent group. Hypertension, diabetes, chronic renal insufficiency and mean age did not differ between the two groups. 'Persistent' patients had higher mortality (HR = 1.26, 95% CI = 0.89���1.78, p = 0.199 when unadjusted and HR = 1.29, 95% CI = 0.89���1.86, p = 0.176 when adjusted for race, LVEF and ischemic etiology) HR for mortality in persistent patients was 1.99 (95% CI = 1.06���3.73, p = 0.03) using the mean method. The following results were found in those with ischemic cardiomyopathy (HR = 1.44034, 95% CI = 0.92���2.26, p = 0.113) and (HR = 1.89, 95% CI = 1.01���3.55, p = 0.046) by using the mean method. 2 out of three patients with HF who were readmitted three or more times had persistent elevation of troponin I levels. Patients with chronic persistence of troponin I elevation showed a trend towards lesser survival as compared to patients who did not have chronic persistence, however this did not reach statistical significance. This trend was seen more among ischemic patients than non ischemic patients, but did not reach statistical significance. With the mean method, patients with chronic persistence of troponin I elevation had significantly lesser survival than those without it. Also ischemic patients had significantly lesser survival than non ischemic patients. ^

Proceedings of the 22nd Annual Biochemical Engineering Symposium

This is the twenty-second of a series of symposia devoted to talks and posters by students about their biochemical engineering research. The first, third, fifth, ninth, twelfth, sixteenth, and twenti~th were hosted by Kansas State University, the second and fourth by the University of Nebraska- Lincoln, the sixth, seventh, tenth, thirteenth, seventeenth, and twenty-second by Iowa State University, the eighth, fourteenth, and nineteenth by the University of Missouri-Columbia, the eleventh, fifteenth, and twenty-first by Colorado State University, and the eighteenth by the University of Colorado. Next year's symposium will be at the University of Oklahoma. Symposium proceedings are edited and issued by faculty of the host institution. Because final publication usually takes place in refereed journals, articles included here are brief and often cover work in progress. ContentsC. A. Baldwin, J.P. McDonald, and L. E. Erickson, Kansas State University. Effect of Hydrocarbon Phase on Kinetic and Transport Limitations for Bioremediation of Microporous Soil J. C. Wang, S. K. Banerji, and Rakesh Bajpai, University of Missouri-Columbia. Migration of PCP in Soil-Columns in Presence of a Second Organic Phase Cheng-Hsien Hsu and Roger G. Harrison, University of Oklahoma. Bacterial Leaching of Zinc and Copper from Mining Wastes James A. Searles, Paul Todd, and Dhinakar S. Kompala, University of Colorado. Suspension Culture of Chinese Hamster Ovary Cells Utilizing Inclined Sedimentation Ron Beyerinck and Eric H. Dunlop, Colorado State University. The Effect of Feed Zone Turbulence as Measured by Laser Doppler Velocimetry on Baker's Yeast Metabolism in a Chemostat Paul Li-Hong Yeh, GraceY. Sun, Gary A. Weisman, and Rakesh Bajpai, University of Missouri-Columbia. Effect of Medium Constituents upon Membrane Composition of Insect Cells R. Shane Gold, M. M. Meagher, R. Hutkins, and T. Conway, University of Nebraska-Lincoin. Ethanol Tolerance and Carbohydrate Metabolism in Lactobacilli John Sargantanis and M. N. Karim, Colorado State University. Application of Kalman Filter and Adaptive Control in Solid Substrate Fermentation D. Vrana, M. Meagher, and R. Hutkins, University of Nebraska-Lincoln. Product Recovery Optimization in the ABE Fermentation Kalyan R. Tadikonda and Robert H. Davis, University of Colorado. Cell Separations Using Targeted Monoclonal Antibodies Against Surface Proteins Meng H. Heng and Charles E. Glatz, Iowa State University. Charged Fusion for Selective Recovery of B-Galactosidase from Cell Extract Using Hollow Fiber Ion-Exchange Membrane Adsorption Hsiu-Mei Chen, Peter J. Reilly, and Clark Ford, Iowa State University. Site-Directed Mutagenesis to Enhance Thermostability of Glucoamylase from Aspergillus: A Rational Approach P. Tuitemwong, L. E. Erickson, and D. Y. C. Fung, Kansas State University. Applications of Enzymatic Hydrolysis and Fermentation on the Reduction of Flatulent Sugars in the Rapid Hydration Hydrothermal Cooked Soy Milk Sanjeev Redkar and Robert H. Davis, University of Colorado. Crossflow Microfiltration of Yeast Suspensions Linda Henk and James C. Linden, Colorado State University, and Irving C. Anderson, Iowa State University. Evaluation of Sorghum Ensilage as an Ethanol Feedstock Marc Lipovitch and James C. Linden, Colorado State University. Stability and Biomass Feedstock Pretreatability for Simultaneous Saccharification and Fermentation Ali Demirci, Anthony L. Pometto Ill, and Kenneth E. Johnson, Iowa State University. Application of Biofilm Reactors in Lactic Acid Fermentation Michael K. Dowd, Peter I. Reilly, and WalterS. Trahanovsky, Iowa State University. Low Molecular-Weight Organic Composition of Ethanol Stillage from Corn Craig E. Forney, Meng H. Heng, John R. Luther, Mark Q. Niederauer, and Charles E. Glatz, Iowa State University. Enhancement of Protein Separation Using Genetic Engineering J. F. Shimp, J. C. Tracy, E. Lee, L. C. Davis, and L. E. Erickson, Kansas State University. Modeling Contaminant Transport, Biodegradation and Uptake by Plants in the Rhizosphere Xiaoqing Yang, L. E. Erickson, and L. T. Fan, Kansas State University. Modeling of Dispersive-Convective Characteristics in Bioremediation of Contaminated Soil Jan Johansson and Rakesh Bajpai, University of Missouri-Columbia. Fouling of Membranes J. M. Wang, S. K. Banerji, and R. K. Bajpai, University of Missouri-Columbia. Migration of Sodium-Pentachorophenol (Na-PCP) in Unsaturated and Saturated Soil-Columns J. Sweeney and M. Meagher, University of Nebraska-Lincoln. The Purification of Alpha-D-Glucuronidase from Trichoderma reesei

Sistematizaci��n de suelos : eficiencia en la ejecuci��n del proyecto en suelos complejos

El manejo sustentable de los recursos naturales relacionados con proyectos de utilizaci��n de los recursos h��dricos (entre otros), requiere en muchos casos de la modificaci��n del relieve existente. Esto conlleva la necesidad de adecuaci��n de la capa homog��nea superior del suelo, operaci��n que suele denominarse &quot;sistematizaci��n&quot;, la cual facilita una distribuci��n m��s uniforme de las lluvias y del agua de riego. Esta modificaci��n de la capa superior del suelo es realizada en base a un proyecto, cuya inclinaci��n responda a las pendientes naturales o a las establecidas por el dise��ador. En la ejecuci��n del dise��o proyectado, en superficies superiores a una hect��rea, el movimiento de tierra se realiza con equipos pesados, que no aseguran un alto porcentaje de eficiencia en lo que al movimiento de tierra se refiere, ya que parte del material se pierde en el acarreo, pero muy especialmente, por la compactaci��n desuniforme del mismo, asociada con las texturas complejas del suelo a trabajar. El presente trabajo determin�� el ��ndice de precisi��n en la ejecuci��n del proyecto de sistematizaci��n a partir de un ��ndice estad��stico internacionalmente aceptado, el &quot;Root Mean Squared Error (RMSE)&quot;, comparando los valores altim��tricos proyectados y los realmente obtenidos luego de la ejecuci��n del proyecto, en tres parcelas con distinta secuencia de labores y maquinaria utilizadas, pero con el mismo tipo de suelo en el ��rea del eje Pilar - La Plata (Argentina). Los resultados obtenidos, que var��an de un RMSE de 4 a 6 cm, permiten concluir, para los sitios y las condiciones estudiadas, que no pueden asegurarse en la sistematizaci��n ��ndices de precisi��n en la ejecuci��n de la obra, inferiores a los 4 cm.

Detection and Tracking of Traffic Signs Using a Recursive Bayesian Decision Framework

In this paper we propose a new method for the automatic detection and tracking of road traffic signs using an on-board single camera. This method aims to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. The proposed approach exploits a combination of different features, such as color, appearance, and tracking information. This information is introduced into a recursive Bayesian decision framework, in which prior probabilities are dynamically adapted to tracking results. This decision scheme obtains a number of candidate regions in the image, according to their HS (Hue-Saturation). Finally, a Kalman filter with an adaptive noise tuning provides the required time and spatial coherence to the estimates. Results have shown that the proposed method achieves high detection rates in challenging scenarios, including illumination changes, rapid motion and significant perspective distortion

Development of a grid connected micro wind generator. A practical activity for the course on electric generation with wind energy

This paper describes a practical activity, part of the renewable energy course where the students have to build their own complete wind generation system, including blades, PM-generator, power electronics and control. After connecting the system to the electric grid the system has been tested during real wind scenarios. The paper will describe the electric part of the work surface-mounted permanent magnet machine design criteria as well as the power electronics part for the power control and the grid connection. A Kalman filter is used for the voltage phase estimation and current commands obtained in order to control active and reactive power. The connection to the grid has been done and active and reactive power has been measured in the system.

PDR with a foot-mounted IMU and ramp detection

The localization of persons in indoor environments is nowadays an open problem. There are partial solutions based on the deployment of a network of sensors (Local Positioning Systems or LPS). Other solutions only require the installation of an inertial sensor on the person���s body (Pedestrian Dead-Reckoning or PDR). PDR solutions integrate the signals coming from an Inertial Measurement Unit (IMU), which usually contains 3 accelerometers and 3 gyroscopes. The main problem of PDR is the accumulation of positioning errors due to the drift caused by the noise in the sensors. This paper presents a PDR solution that incorporates a drift correction method based on detecting the access ramps usually found in buildings. The ramp correction method is implemented over a PDR framework that uses an Inertial Navigation algorithm (INS) and an IMU attached to the person���s foot. Unlike other approaches that use external sensors to correct the drift error, we only use one IMU on the foot. To detect a ramp, the slope of the terrain on which the user is walking, and the change in height sensed when moving forward, are estimated from the IMU. After detection, the ramp is checked for association with one of the existing in a database. For each associated ramp, a position correction is fed into the Kalman Filter in order to refine the INS-PDR solution. Drift-free localization is achieved with positioning errors below 2 meters for 1,000-meter-long routes in a building with a few ramps.

Localization and activity detection Based on the fusion of environment And inertial sensors = Localizaci��n y detecci��n de actividad Basadas en integraci��n de sensores y dispositivos inerciales

Los sensores inerciales (aceler��metros y gir��scopos) se han ido introduciendo poco a poco en dispositivos que usamos en nuestra vida diaria gracias a su minituarizaci��n. Hoy en d��a todos los smartphones contienen como m��nimo un aceler��metro y un magnet��metro, siendo complementados en losm��s modernos por gir��scopos y bar��metros. Esto, unido a la proliferaci��n de los smartphones ha hecho viable el dise��o de sistemas basados en las medidas de sensores que el usuario lleva colocados en alguna parte del cuerpo (que en un futuro estar��n contenidos en tejidos inteligentes) o los integrados en su m��vil. El papel de estos sensores se ha convertido en fundamental para el desarrollo de aplicaciones contextuales y de inteligencia ambiental. Algunos ejemplos son el control de los ejercicios de rehabilitaci��n o la oferta de informaci��n referente al sitio tur��stico que se est�� visitando. El trabajo de esta tesis contribuye a explorar las posibilidades que ofrecen los sensores inerciales para el apoyo a la detecci��n de actividad y la mejora de la precisi��n de servicios de localizaci��n para peatones. En lo referente al reconocimiento de la actividad que desarrolla un usuario, se ha explorado el uso de los sensores integrados en los dispositivos m��viles de ��ltima generaci��n (luz y proximidad, aceler��metro, gir��scopo y magnet��metro). Las actividades objetivo son conocidas como ���at��micas��� (andar a distintas velocidades, estar de pie, correr, estar sentado), esto es, actividades que constituyen unidades de actividades m��s complejas como pueden ser lavar los platos o ir al trabajo. De este modo, se usan algoritmos de clasificaci��n sencillos que puedan ser integrados en un m��vil como el Na��ve Bayes, Tablas y ��rboles de Decisi��n. Adem��s, se pretende igualmente detectar la posici��n en la que el usuario lleva el m��vil, no s��lo con el objetivo de utilizar esa informaci��n para elegir un clasificador entrenado s��lo con datos recogidos en la posici��n correspondiente (estrategia que mejora los resultados de estimaci��n de la actividad), sino tambi��n para la generaci��n de un evento que puede producir la ejecuci��n de una acci��n. Finalmente, el trabajo incluye un an��lisis de las prestaciones de la clasificaci��n variando el tipo de par��metros y el n��mero de sensores usados y teniendo en cuenta no s��lo la precisi��n de la clasificaci��n sino tambi��n la carga computacional. Por otra parte, se ha propuesto un algoritmo basado en la cuenta de pasos utilizando informaiii ci��n proveniente de un aceler��metro colocado en el pie del usuario. El objetivo final es detectar la actividad que el usuario est�� haciendo junto con la estimaci��n aproximada de la distancia recorrida. El algoritmo de cuenta pasos se basa en la detecci��n de m��ximos y m��nimos usando ventanas temporales y umbrales sin requerir informaci��n espec��fica del usuario. El ��mbito de seguimiento de peatones en interiores es interesante por la falta de un est��ndar de localizaci��n en este tipo de entornos. Se ha dise��ado un filtro extendido de Kalman centralizado y ligeramente acoplado para fusionar la informaci��n medida por un aceler��metro colocado en el pie del usuario con medidas de posici��n. Se han aplicado tambi��n diferentes t��cnicas de correcci��n de errores como las de velocidad cero que se basan en la detecci��n de los instantes en los que el pie est�� apoyado en el suelo. Los resultados han sido obtenidos en entornos interiores usando las posiciones estimadas por un sistema de triangulaci��n basado en la medida de la potencia recibida (RSS) y GPS en exteriores. Finalmente, se han implementado algunas aplicaciones que prueban la utilidad del trabajo desarrollado. En primer lugar se ha considerado una aplicaci��n de monitorizaci��n de actividad que proporciona al usuario informaci��n sobre el nivel de actividad que realiza durante un per��odo de tiempo. El objetivo final es favorecer el cambio de comportamientos sedentarios, consiguiendo h��bitos saludables. Se han desarrollado dos versiones de esta aplicaci��n. En el primer caso se ha integrado el algoritmo de cuenta pasos en una plataforma OSGi m��vil adquiriendo los datos de un aceler��metro Bluetooth colocado en el pie. En el segundo caso se ha creado la misma aplicaci��n utilizando las implementaciones de los clasificadores en un dispositivo Android. Por otro lado, se ha planteado el dise��o de una aplicaci��n para la creaci��n autom��tica de un diario de viaje a partir de la detecci��n de eventos importantes. Esta aplicaci��n toma como entrada la informaci��n procedente de la estimaci��n de actividad y de localizaci��n adem��s de informaci��n almacenada en bases de datos abiertas (fotos, informaci��n sobre sitios) e informaci��n sobre sensores reales y virtuales (agenda, c��mara, etc.) del m��vil. Abstract Inertial sensors (accelerometers and gyroscopes) have been gradually embedded in the devices that people use in their daily lives thanks to their miniaturization. Nowadays all smartphones have at least one embedded magnetometer and accelerometer, containing the most upto- date ones gyroscopes and barometers. This issue, together with the fact that the penetration of smartphones is growing steadily, has made possible the design of systems that rely on the information gathered by wearable sensors (in the future contained in smart textiles) or inertial sensors embedded in a smartphone. The role of these sensors has become key to the development of context-aware and ambient intelligent applications. Some examples are the performance of rehabilitation exercises, the provision of information related to the place that the user is visiting or the interaction with objects by gesture recognition. The work of this thesis contributes to explore to which extent this kind of sensors can be useful to support activity recognition and pedestrian tracking, which have been proven to be essential for these applications. Regarding the recognition of the activity that a user performs, the use of sensors embedded in a smartphone (proximity and light sensors, gyroscopes, magnetometers and accelerometers) has been explored. The activities that are detected belong to the group of the ones known as ���atomic��� activities (e.g. walking at different paces, running, standing), that is, activities or movements that are part of more complex activities such as doing the dishes or commuting. Simple, wellknown classifiers that can run embedded in a smartphone have been tested, such as Na��ve Bayes, Decision Tables and Trees. In addition to this, another aim is to estimate the on-body position in which the user is carrying the mobile phone. The objective is not only to choose a classifier that has been trained with the corresponding data in order to enhance the classification but also to start actions. Finally, the performance of the different classifiers is analysed, taking into consideration different features and number of sensors. The computational and memory load of the classifiers is also measured. On the other hand, an algorithm based on step counting has been proposed. The acceleration information is provided by an accelerometer placed on the foot. The aim is to detect the activity that the user is performing together with the estimation of the distance covered. The step counting strategy is based on detecting minima and its corresponding maxima. Although the counting strategy is not innovative (it includes time windows and amplitude thresholds to prevent under or overestimation) no user-specific information is required. The field of pedestrian tracking is crucial due to the lack of a localization standard for this kind of environments. A loosely-coupled centralized Extended Kalman Filter has been proposed to perform the fusion of inertial and position measurements. Zero velocity updates have been applied whenever the foot is detected to be placed on the ground. The results have been obtained in indoor environments using a triangulation algorithm based on RSS measurements and GPS outdoors. Finally, some applications have been designed to test the usefulness of the work. The first one is called the ���Activity Monitor��� whose aim is to prevent sedentary behaviours and to modify habits to achieve desired objectives of activity level. Two different versions of the application have been implemented. The first one uses the activity estimation based on the step counting algorithm, which has been integrated in an OSGi mobile framework acquiring the data from a Bluetooth accelerometer placed on the foot of the individual. The second one uses activity classifiers embedded in an Android smartphone. On the other hand, the design of a ���Travel Logbook��� has been planned. The input of this application is the information provided by the activity and localization modules, external databases (e.g. pictures, points of interest, weather) and mobile embedded and virtual sensors (agenda, camera, etc.). The aim is to detect important events in the journey and gather the information necessary to store it as a journal page.

Modal contribution and state space order selection in operational modal analysis

The estimation of modal parameters of a structure from ambient measurements has attracted the attention of many researchers in the last years. The procedure is now well established and the use of state space models, stochastic system identification methods and stabilization diagrams allows to identify the modes of the structure. In this paper the contribution of each identified mode to the measured vibration is discussed. This modal contribution is computed using the Kalman filter and it is an indicator of the importance of the modes. Also the variation of the modal contribution with the order of the model is studied. This analysis suggests selecting the order for the state space model as the order that includes the modes with higher contribution. The order obtained using this method is compared to those obtained using other well known methods, like Akaike criteria for time series or the singular values of the weighted projection matrix in the Stochastic Subspace Identification method. Finally, both simulated and measured vibration data are used to show the practicability of the derived technique. Finally, it is important to remark that the method can be used with any identification method working in the state space model.

Improved heuristic drift elimination with magnetically-aided dominant directions (MiHDE) for pedestrian navigation in complex buildings

The main problem of pedestrian dead-reckoning (PDR) using only a body-attached inertial measurement unit is the accumulation of heading errors. The heading provided by magnetometers in indoor buildings is in general not reliable and therefore it is commonly not used. Recently, a new method was proposed called heuristic drift elimination (HDE) that minimises the heading error when navigating in buildings. It assumes that the majority of buildings have their corridors parallel to each other, or they intersect at right angles, and consequently most of the time the person walks along a straight path with a heading constrained to one of the four possible directions. In this article we study the performance of HDE-based methods in complex buildings, i.e. with pathways also oriented at 45��, long curved corridors, and wide areas where non-oriented motion is possible. We explain how the performance of the original HDE method can be deteriorated in complex buildings, and also, how severe errors can appear in the case of false matches with the building's dominant directions. Although magnetic compassing indoors has a chaotic behaviour, in this article we analyse large data-sets in order to study the potential use that magnetic compassing has to estimate the absolute yaw angle of a walking person. Apart from these analysis, this article also proposes an improved HDE method called Magnetically-aided Improved Heuristic Drift Elimination (MiHDE), that is implemented over a PDR framework that uses foot-mounted inertial navigation with an extended Kalman filter (EKF). The EKF is fed with the MiHDE-estimated orientation error, gyro bias corrections, as well as the confidence over that corrections. We experimentally evaluated the performance of the proposed MiHDE-based PDR method, comparing it with the original HDE implementation. Results show that both methods perform very well in ideal orthogonal narrow-corridor buildings, and MiHDE outperforms HDE for non-ideal trajectories (e.g. curved paths) and also makes it robust against potential false dominant direction matchings.