14,185 research outputs found

    Position estimation delays in signal injection-based sensorless PMSM drives

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    The causes of position estimation delays and their effects on the sensorless control of permanent magnet synchronous motor drives are investigated. The position of a permanent magnet synchronous machine is estimated via the injection of high frequency voltage signals. The delays under investigation are due to the digital implementation of the control algorithm and to the digital filters adopted for decoupling the inspection signals from the fundamental components of the stator current measures. If not correctly modeled and compensated, such delays can reduce the performance of the control scheme. Experimental results are provided, proving the accuracy of the modeling approach and the effectiveness of the related compensation strateg

    Improved mirror position estimation using resonant quantum smoothing

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    Quantum parameter estimation, the ability to precisely obtain a classical value in a quantum system, is very important to many key quantum technologies. Many of these technologies rely on an optical probe, either coherent or squeezed states to make a precise measurement of a parameter ultimately limited by quantum mechanics. We use this technique to theoretically model, simulate and validate by experiment the measurement and precise estimation of the position of a cavity mirror. In non-resonant systems, the achieved estimation enhancement from quantum smoothing over optimal filtering has not exceeded a factor two, even when squeezed state probes were used. Using a coherent state probe, we show that using quantum smoothing on a mechanically resonant structure driven by a resonant forcing function can result significantly greater improvement in parameter estimation than with non-resonant systems. In this work, we show that it is possible to achieve a smoothing improvement by a factor in excess of three times over optimal filtering. By using intra-cavity light as the probe we obtain finer precision than has been achieved with the equivalent quantum resources in free-space.Comment: 14 pages, 9 figures and 1 tabl

    Indoor localization based on multiple LEDs position estimation

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    This paper describes the simulation results and hardware implementation of an inexpensive, low-complexity LED based indoor positioning system. Localization by multiple LEDs estimation model (MLEM) approximates position of a mobile receiver by the acquisition of positional information from LED transmitters. Multiple LED orientation can either be with or without overlap. Receivers in a no-overlap LED orientation experience only single access while multiple access receivers are designed for orientations with overlaps. Single and multiple access systems were developed and implemented by the use of low cost ATMEG 328 microcontroller. Since multiple LEDs transmit data at the same wavelength and are asynchronous, overlap in multiple access system causes interference. The possibility of this interference is reduced by packet based pulse duration multiplexing (PDM) and a low duty cycle transmission protocol. By the use of MLEM, root mean square error in position estimation is reduced to about 1 percent of the length an indoor location. Experimental results show that overlap increases positional accuracy over a wider coverage region and that the multiple access system allows for a more reliable positioning

    Mitigation of cross-saturation effects in resonance-based sensorless switched reluctance drives

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    The stator and rotor yoke in a switched reluctance motor form magnetic circuit parts that are typically shared by different phases. If these parts saturate due to the excitation of one phase, this will lead to a change of the magnetic characteristics of all other phases sharing these parts. In several position-sensorless methods, cross-saturation leads to a load-dependent position estimation error. In this paper, the influence of cross-saturation on a resonance-based position estimation method is studied. The method extracts position information from electrical resonances triggered in an idle motor phase. A cross-saturation mitigation scheme is presented in order to reduce the commutation position error. The scheme uses only one additional parameter per phase which can be measured automatically during commissioning of the drive. Experimental results at low and medium speed show that the position estimation error remains smaller dan 2 mechanical degrees over the rated load range

    Quality-Aware Broadcasting Strategies for Position Estimation in VANETs

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    The dissemination of vehicle position data all over the network is a fundamental task in Vehicular Ad Hoc Network (VANET) operations, as applications often need to know the position of other vehicles over a large area. In such cases, inter-vehicular communications should be exploited to satisfy application requirements, although congestion control mechanisms are required to minimize the packet collision probability. In this work, we face the issue of achieving accurate vehicle position estimation and prediction in a VANET scenario. State of the art solutions to the problem try to broadcast the positioning information periodically, so that vehicles can ensure that the information their neighbors have about them is never older than the inter-transmission period. However, the rate of decay of the information is not deterministic in complex urban scenarios: the movements and maneuvers of vehicles can often be erratic and unpredictable, making old positioning information inaccurate or downright misleading. To address this problem, we propose to use the Quality of Information (QoI) as the decision factor for broadcasting. We implement a threshold-based strategy to distribute position information whenever the positioning error passes a reference value, thereby shifting the objective of the network to limiting the actual positioning error and guaranteeing quality across the VANET. The threshold-based strategy can reduce the network load by avoiding the transmission of redundant messages, as well as improving the overall positioning accuracy by more than 20% in realistic urban scenarios.Comment: 8 pages, 7 figures, 2 tables, accepted for presentation at European Wireless 201

    Distributed Recognition of Reference Nodes for Wireless Sensor Network Localization

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    All known localization techniques for wireless sensor and ad-hoc networks require certain set of reference nodes being used for position estimation. The anchor-free techniques in contrast to anchor-based do not require reference nodes called anchors to be placed in the network area before localization operation itself, but they can establish own reference coordinate system to be used for the relative position estimation. We observed that contemporary anchor-free localization algorithms achieve a low localization error, but dissipate significant energy reserves during the recognition of reference nodes used for the position estimation. Therefore, we have proposed the optimized anchor-free localization algorithm referred to as BRL (Boundary Recognition aided Localization), which achieves a low localization error and mainly reduces the communication cost of the reference nodes recognition phase. The proposed BRL algorithm was investigated throughout the extensive simulations on the database of networks with the different number of nodes and densities and was compared in terms of communication cost and localization error with the known related algorithms such as AFL and CRP. Through the extensive simulations we have observed network conditions where novel BRL algorithm excels in comparison with the state of art

    Satellite-map position estimation for the Mars rover

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    A method for locating the Mars rover using an elevation map generated from satellite data is described. In exploring its environment, the rover is assumed to generate a local rover-centered elevation map that can be used to extract information about the relative position and orientation of landmarks corresponding to local maxima. These landmarks are integrated into a stochastic map which is then matched with the satellite map to obtain an estimate of the robot's current location. The landmarks are not explicitly represented in the satellite map. The results of the matching algorithm correspond to a probabilistic assessment of whether or not the robot is located within a given region of the satellite map. By assigning a probabilistic interpretation to the information stored in the satellite map, researchers are able to provide a precise characterization of the results computed by the matching algorithm
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