894 resultados para robust extended kalman filter
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Analog filters and direct digital filters are implemented using digital signal processing techniques. Specifically, Butterworth, Elliptic, and Chebyshev filters are implemented using the Motorola 56001 Digital Signal Processor by the integration of three software packages: MATLAB, C++, and Motorola's Application Development System. The integrated environment allows the novice user to design a filter automatically by specifying the filter order and critical frequencies, while permitting more experienced designers to take advantage of MATLAB's advanced design capabilities. This project bridges the gap between the theoretical results produced by MATLAB and the practicalities of implementing digital filters using the Motorola 56001 Digital Signal Processor. While these results are specific to the Motorola 56001 they may be extended to other digital signal processors. MATLAB handles the filter calculations, a C++ routine handles the conversion to assembly code, and the Motorola software compiles and transmits the code to the processor
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Thrombosis of the inferior vena cava is a life-threatening complication in cancer patients leading to pulmonary embolism. These patients can also be affected by superior vena cava syndrome causing dyspnea followed by trunk or extremity swelling. We report the case of a 61-year-old female suffering from an extended colorectal tumor who became affected by both of the mentioned complications. Due to thrombus formation within the right vena jugularis interna, thrombosis of the inferior vena cava, and superior vena cava syndrome, a combined interventional procedure via a left jugular access with stenting of the superior vena cava and filter placement into the inferior vena cava was performed As a consequence, relief of the patient's symptoms, prevention of pulmonary embolism, and paving of the way for further venous chemotherapy were achieved.
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Many location-based services target users in indoor environments. Similar to the case of dense urban areas where many obstacles exist, indoor localization techniques suffer from outlying measurements caused by severe multipath propaga??tion and non-line-of-sight (NLOS) reception. Obstructions in the signal path caused by static or mobile objects downgrade localization accuracy. We use robust multipath mitigation techniques to detect and filter out outlying measurements in indoor environments. We validate our approach using a power-based lo??calization system with GSM. We conducted experiments without any prior knowledge of the tracked device's radio settings or the indoor radio environment. We obtained localization errors in the range of 3m even if the sensors had NLOS links to the target device.
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The paper presents a method to analyze robust stability and transient performance of a distributed power system consisting of commercial converter modules interconnected through a common input filter. The method is based on the use of four transfer functions, which are measurable from the converter input and output terminals. It is shown that these parameters provide important information on the power module sensitivity to the interactions caused by the external impedances. Practical characterization for the described system structure is performed introducing special transfer functions utilized for the interactions assessment. Experimental results are provided to support the presented analysis procedure.
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Pulse-width modulation is widely used to control electronic converters. One of the most frequently used topologies for high DC voltage/low DC voltage conversion is the Buck converter. These converters are described by a second order system with an LC filter between the switching subsystem and the load. The use of a coil with an amorphous magnetic material core rather than an air core permits the design of smaller converters. If high switching frequencies are used to obtain high quality voltage output, then the value of the auto inductance L is reduced over time. Robust controllers are thus needed if the accuracy of the converter response must be preserved under auto inductance and payload variations. This paper presents a robust controller for a Buck converter based on a state space feedback control system combined with an additional virtual space variable which minimizes the effects of the inductance and load variations when a switching frequency that is not too high is applied. The system exhibits a null steady-state average error response for the entire range of parameter variations. Simulation results and a comparison with a standard PID controller are also presented.
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This article describes the design of a linear observer–linear controller-based robust output feedback scheme for output reference trajectory tracking tasks in the case of nonlinear, multivariable, nonholonomic underactuated mobile manipulators. The proposed linear feedback scheme is based on the use of a classical linear feedback controller and suitably extended, high-gain, linear Generalized Proportional Integral (GPI) observers, thus aiding the linear feedback controllers to provide an accurate simultaneous estimation of each flat output associated phase variables and of the exogenous and perturbation inputs. This information is used in the proposed feedback controller in (a) approximate, yet close, cancelations, as lumped unstructured time-varying terms, of the influence of the highly coupled nonlinearities, and (b) the devising of proper linear output feedback control laws based on the approximate estimates of the string of phase variables associated with the flat outputs simultaneously provided by the disturbance observers. Simulations reveal the effectiveness of the proposed approach.
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In this paper we present an adaptive spatio-temporal filter that aims to improve low-cost depth camera accuracy and stability over time. The proposed system is composed by three blocks that are used to build a reliable depth map of static scenes. An adaptive joint-bilateral filter is used to obtain consistent depth maps by jointly considering depth and video information and by adapting its parameters to different levels of estimated noise. Kalman filters are used to reduce the temporal random fluctuations of the measurements. Finally an interpolation algorithm is used to obtain consistent depth maps in the regions where the depth information is not available. Results show that this approach allows to considerably improve the depth maps quality by considering spatio-temporal information and by adapting its parameters to different levels of noise.
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A new method for fitting a series of Zernike polynomials to point clouds defined over connected domains of arbitrary shape defined within the unit circle is presented in this work. The method is based on the application of machine learning fitting techniques by constructing an extended training set in order to ensure the smooth variation of local curvature over the whole domain. Therefore this technique is best suited for fitting points corresponding to ophthalmic lenses surfaces, particularly progressive power ones, in non-regular domains. We have tested our method by fitting numerical and real surfaces reaching an accuracy of 1 micron in elevation and 0.1 D in local curvature in agreement with the customary tolerances in the ophthalmic manufacturing industry.
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Automatically generating maps of a measured variable of interest can be problematic. In this work we focus on the monitoring network context where observations are collected and reported by a network of sensors, and are then transformed into interpolated maps for use in decision making. Using traditional geostatistical methods, estimating the covariance structure of data collected in an emergency situation can be difficult. Variogram determination, whether by method-of-moment estimators or by maximum likelihood, is very sensitive to extreme values. Even when a monitoring network is in a routine mode of operation, sensors can sporadically malfunction and report extreme values. If this extreme data destabilises the model, causing the covariance structure of the observed data to be incorrectly estimated, the generated maps will be of little value, and the uncertainty estimates in particular will be misleading. Marchant and Lark [2007] propose a REML estimator for the covariance, which is shown to work on small data sets with a manual selection of the damping parameter in the robust likelihood. We show how this can be extended to allow treatment of large data sets together with an automated approach to all parameter estimation. The projected process kriging framework of Ingram et al. [2007] is extended to allow the use of robust likelihood functions, including the two component Gaussian and the Huber function. We show how our algorithm is further refined to reduce the computational complexity while at the same time minimising any loss of information. To show the benefits of this method, we use data collected from radiation monitoring networks across Europe. We compare our results to those obtained from traditional kriging methodologies and include comparisons with Box-Cox transformations of the data. We discuss the issue of whether to treat or ignore extreme values, making the distinction between the robust methods which ignore outliers and transformation methods which treat them as part of the (transformed) process. Using a case study, based on an extreme radiological events over a large area, we show how radiation data collected from monitoring networks can be analysed automatically and then used to generate reliable maps to inform decision making. We show the limitations of the methods and discuss potential extensions to remedy these.
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This research is concerned with the development of distributed real-time systems, in which software is used for the control of concurrent physical processes. These distributed control systems are required to periodically coordinate the operation of several autonomous physical processes, with the property of an atomic action. The implementation of this coordination must be fault-tolerant if the integrity of the system is to be maintained in the presence of processor or communication failures. Commit protocols have been widely used to provide this type of atomicity and ensure consistency in distributed computer systems. The objective of this research is the development of a class of robust commit protocols, applicable to the coordination of distributed real-time control systems. Extended forms of the standard two phase commit protocol, that provides fault-tolerant and real-time behaviour, were developed. Petri nets are used for the design of the distributed controllers, and to embed the commit protocol models within these controller designs. This composition of controller and protocol model allows the analysis of the complete system in a unified manner. A common problem for Petri net based techniques is that of state space explosion, a modular approach to both the design and analysis would help cope with this problem. Although extensions to Petri nets that allow module construction exist, generally the modularisation is restricted to the specification, and analysis must be performed on the (flat) detailed net. The Petri net designs for the type of distributed systems considered in this research are both large and complex. The top down, bottom up and hybrid synthesis techniques that are used to model large systems in Petri nets are considered. A hybrid approach to Petri net design for a restricted class of communicating processes is developed. Designs produced using this hybrid approach are modular and allow re-use of verified modules. In order to use this form of modular analysis, it is necessary to project an equivalent but reduced behaviour on the modules used. These projections conceal events local to modules that are not essential for the purpose of analysis. To generate the external behaviour, each firing sequence of the subnet is replaced by an atomic transition internal to the module, and the firing of these transitions transforms the input and output markings of the module. Thus local events are concealed through the projection of the external behaviour of modules. This hybrid design approach preserves properties of interest, such as boundedness and liveness, while the systematic concealment of local events allows the management of state space. The approach presented in this research is particularly suited to distributed systems, as the underlying communication model is used as the basis for the interconnection of modules in the design procedure. This hybrid approach is applied to Petri net based design and analysis of distributed controllers for two industrial applications that incorporate the robust, real-time commit protocols developed. Temporal Petri nets, which combine Petri nets and temporal logic, are used to capture and verify causal and temporal aspects of the designs in a unified manner.
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We present a thorough study on the development of a polymer optical fibre-based tuneable filter utilizing an intra-core Bragg grating that is electrically tuneable, operating at 1.55 µm. The Bragg grating is made tuneable using a thin-film resistive heater deposited on the surface of the fibre. The polymer fibre was coated via the photochemical deposition of a Pd/Cu metallic layer with the procedure induced by VUV radiation at room temperature. The resulting device, when wavelength tuned via Joule heating, underwent a wavelength shift of 2 nm for a moderate input power of 160 mW, a wavelength to input power coefficient of -13.4 pm mW-1 and time constant of 1.7 s-1. A basic theoretical study verified that for this fibre type one can treat the device as a one-dimensional system. The model was extended to include the effect of input electrical power changes on the refractive index of the fibre and subsequently to changes in the Bragg wavelength of the grating, showing excellent agreement with the experimental measurements.
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We describe in the letter a technique for making extended-range interferometric measurements with a coherence multiplexed system by means of a variation on the dual-wavelength technique. The interferometer is illuminated with a single source and the two wavelengths are synthesised at the output by means of an interference filter.
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We demonstrate an all-fiber-integrated Er-doped fiber laser operating in the soliton-similariton mode-locking regime. In the similariton part of the cavity, a self-similarly evolving parabolic pulse with highly linear chirp propagates in the presence of normal dispersion. Following an in-line fiber-based birefringent filter, the pulse evolves into a soliton in the part of the cavity with anomalous dispersion. The similariton and the soliton pulses are dechirped to 75.5 and 167.2 fs, respectively, outside of the cavity. Mode-locked operation is very robust, owing to the influence of the two similariton and soliton attractors that predominate each half of the laser cavity. The experimental results are supported with numerical simulations, which provide good agreement.
Resumo:
We present a thorough study on the development of a polymer optical fibre-based tuneable filter utilizing an intra-core Bragg grating that is electrically tuneable, operating at 1.55 νm. The Bragg grating is made tuneable using a thin-film resistive heater deposited on the surface of the fibre. The polymer fibre was coated via the photochemical deposition of a Pd/Cu metallic layer with the procedure induced by VUV radiation at room temperature. The resulting device, when wavelength tuned via Joule heating, underwent a wavelength shift of 2 nm for a moderate input power of 160 mW, a wavelength to input power coefficient of -13.4 pm mW-1 and time constant of 1.7 s-1. A basic theoretical study verified that for this fibre type one can treat the device as a one-dimensional system. The model was extended to include the effect of input electrical power changes on the refractive index of the fibre and subsequently to changes in the Bragg wavelength of the grating, showing excellent agreement with the experimental measurements. © 2007 IOP Publishing Ltd.
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Im Rahmen dieser Arbeit wird die Herstellung von miniaturisierten NIR-Spektrometern auf Basis von Fabry-Pérot (FP) Filter Arrays behandelt. Bisher ist die kostengünstige Strukturierung von homogenen und vertikal erweiterten Kavitäten für NIR FP-Filter mittels Nanoimprint Technologie noch nicht verfügbar, weil die Qualität der Schichten des Prägematerials unzureichend ist und die geringe Mobilität der Prägematerialien nicht ausreicht, um die vertikal erweiterten Kavitäten zu füllen. Diese Arbeit konzentriert sich auf die Reduzierung des technischen Aufwands zur Herstellung von homogenen und vertikal erweiterten Kavitäten. Zur Strukturierung der Kavitäten wird ein großflächiger substratkonformer UV-Nanoimprint Prozess (SCIL - Substrate Conformal Imprint Lithoghaphy) verwendet, der auf einem Hybridstempel basiert und Vorteile von harten und weichen Stempeln vereint. Um die genannten Limitierungen zu beseitigen, werden alternative Designs der Kavitäten untersucht und ein neues Prägematerial eingesetzt. Drei Designlösungen zur Herstellung von homogenen und erweiterten Kavitäten werden untersucht und verglichen: (i) Das Aufbringen des Prägematerials mittel mehrfacher Rotationsbeschichtung, um eine höhere Schichtdicke des Prägematerials vor dem Prägeprozess zu erzeugen, (ii) die Verwendung einer hybriden Kavität bestehend aus einer strukturierten Schicht des Prägematerials eingebettet zwischen zwei Siliziumoxidschichten, um die Schichtdicke der organischen Kavität zu erweitern und (iii) die Optimierung des Prägeprozesses durch Verwendung eines neuen Prägematerials. Die mit diesen drei Ansätzen hergestellten FP-Filter Arrays zeigen, hohe Transmissionen (beste Transmission > 90%) und kleine Linienbreiten (Halbwertsbreiten <5 nm).