The role of initial state reconstruction in short and long time deviations from exponential decay

We consider the role of the reconstruction of the initial state in the deviation from exponential decay at short and long times. The long time decay can be attributed to a wave that was, in a classical-like, probabilistic sense, fully outside the initial state or the inner region at intermediate times, i.e., to a completely reconstructed state, whereas the decay during the exponential regime is due instead to a non-reconstructed wave. At short times quantum interference between regenerated and non-regenerated paths is responsible for the deviation from the exponential decay. We may thus conclude that state reconstruction is a ``consistent history'' for long time deviations but not for short ones.Comment: 4 pages, 6 figure

State estimation of induction motor using unscented Kalman filter

In this paper, a new estimation technique, unscented Kalman filter (UKF) is applied to state observation in field oriented control (FOC) of induction motor. UKF, a recent derivative-free nonlinear estimation tool, is used for estimating rotor speed and fluxes using sensed stator current and voltages. In the simulations, UKF, whose several intrinsic properties suggest its use over EKF in highly nonlinear systems, turned out to be very similar to EKF in flux estimates. The simulation results also show that UKF has slightly better speed estimation performance than EKF while driven under the identical machine model and parameters (covariances)

A fuzzy colour quantizer for renderers

WOS: 000077377900002This paper presents a new colour quantization method for ray tracing. Normally, quantization is carried out by generating statistics about the colours present in the original image. Then a colour look-up table is created which contains the colours available in the quantized image. Original quantized values are mapped into the nearest colour entries in the look-up table. Although the execution time is quick using this method (histogram analysis) the cost is that the image quality is poor. The fuzzy c-means clustering algorithm (FCM) is an alternative solution to ameliorate the degradation in image quality. However, FCM introduces a considerable amount of computational burden and the process is time-consuming. This paper shows that the dominant peaks of histograms yield the fuzzy centroids needed for the first estimate in FCM. This reduces the computational burden imposed by FCM and improves the overall execution time. (C) 1998 Elsevier Science B.V. All rights reserved

An ergonomic rendering system for industrial design

7th International Conference on Human-Computer Interaction (HCI International 97) -- AUG 24-29, 1997 -- SAN FRANCISCO, CAWOS: 000072153000148Product design is one of the most important stages in production processes depending on commercial aims and current technology. Success in modelling the products guarantees that customers' requests can be supplied by these products. Aim of using solid modelling techniques in industrial product design is getting realistic models of products in computer environments in such a way that manufacturers could obtain enough information on the products without having to manufacture them. Execution time and quality of the solid modelling technique used in the produce design influence the total production time and quality. Solid modelling techniques based on visual realism increases the time spent on product modelling. Nevertheless, the techniques based on fast execution time generate low-quality solid models of products. Study tries to design a rendering system based on visual realism with an acceptable run-time efficiency. For that reason, a software accelerator is designed in order to accelerate the rendering process. This program implemented by using object oriented programming techniques has a user-friendly and interactive environment between the rendering system and the designers.Chinese Acad Sci, EEC, European Strateg Programme Res & Dev Informat Technol, ESPRIT, Human Factors & Ergon Soc, IEEE Syst Man & Cybernet Soc, Japan Ergon Soc, Japan Management Asso

A comparative study on Kalman filtering techniques designed for state estimation of industrial AC drive systems

In this paper, two different Kalman Filtering techniques, Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF) are investigated and compared both experimentally and theoretically. These non-linear, stochastic observers are employed as a state estimation tool in field-oriented control (FOC) of sensorless AC drives in this work. Using the superiorities of Kalman filtering, rotor speed and dq-axis fluxes of an induction motor are estimated only with the sensed stator currents and voltages information. In order to compare the estimation performances of the observers explicitly, both of the observers are designed for the same motor model and run with the same covariance matrices under the same conditions. In the simulation results it is shown that, UKF, whose several intrinsic properties suggest its use over EKF in highly nonlinear systems, has more satisfactory rotor speed and flux estimates, which are the most critical states for FOC. These simulation results are supported with experimental results

Robot mimicking: A visual approach for human machine interaction

The proposed method is the preliminary step for a human-machine interaction system, in which a robot arm mimics the movements of a human arm, visualized through a camera set-up. In order to achieve this goal, the posture of a model joint, which simulates a human arm, is determined by finding the bending and yaw angles from captured images. The image analysis steps consist of preprocessing of noise via median filtering, thresholding and connected component analysis. The relation between the relative positions of these markers can be used to determine the unknown bending and yaw angles of the model joint. This information is further passed to a PUMA 760 robot arm to finalize the goal. The preliminary simulation results are promising to present that the proposed system can be utilized in a real environment in which a human (arm) can be mimicked by a machine with visual sensor

Bilinmeyen değişken ortamda modelleyerek irdeleme ve öğrenme yöntemleriyle nesnelerin değişik algılayıcılardan bilgi füzyonu elde edilerek tanımlanması

TÜBİTAK MİSAG31.07.1993Rapor "Bilinmeyen Değişken Ortamda. Modelleyerek İrdeleme ve Öğrenme Yöntemleriyle Nesnelerin Değişik Algılayıcılardan Gelen Bilginin Birleştlrimi Yoluyla Tanımlanması" konusunda yapılan çalışmaları özetlemektedir. Birden çok algılayıcıdan edinilen bilgilerdeki cluyaçlardan ileri gelen belirsizlikler ve gürültü önce en aza indirgenmekledir. Burada önişlem algoritmaları kullanılmaktadır. Duyaç bilgisindeki belirsizlik ve eksilikler diğer duyanlardan, elde olunanlarla tamamlanmakta sonuçtaki görüntünün taşıdığı bilginin tama yakın olması sağlanmaktadır. Bundan sonra görüntü üzerinde nesne tanıma algoritmaları uygulanmaktadır. Nesne tanıma, kenar çizgisi belirlenmiş nesne örüntüleri. üzerine inşa edilmiştir. Nesnenin kenar çizgisi, bu çizginin boyu, orunlunun ağırlık merkezi, ve birinci ve ikinci momentlerin bellekteki modelde tanımlananlarla karşılaştırılmasıyla tanıma işlemi tamamlanmaktadır. Tanınamayan yeni bir nesne örüntüsü ve ilişkili bilgiler yeni bir nesne olarak tanımlanmaktadır. Sisteme bu yöntemle öğrenebilir bir yapı kazandırılmştır. Gerçekleştirilen donanımsal yapıda ultrasonik duyaç dizisi bir robot kol bileğine bağlanmış tüm tarayarak alınacak görüntü kol bir tür süpürme hareketi sonucunda alınmaktadır. Kol bu işlemi takiben üzerinde işlem görülecek nesneleri tanıyıp, yerlerini ve duruş biçim ve yönlerini belirledikten sonra gerekli, manevralara başlayabilecektir. Bu ise kolun yörünge planlamasının yapılmasına ilişkin çalışmalara konu olmaktadır. Çalışma ekinde çalışma sürecinde yapılmış olan yayınların (Türkçe) birer kopyası verilmektedir