201 resultados para Prosthetic Motor Imaginary Task


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An experimental evaluation of small two-phase induction motor drives operating with different inverter topologies is described. Results show that a PWM-based four-switch inverter, having only low-side switches is attractive for high-speed low-cost applications where speeds greater than those that can be obtained using single phase induction motors are required.

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This paper demonstrates how a finite element model which exploits domain decomposition is applied to the analysis of three-phase induction motors. It is shown that a significant gain in cpu time results when compared with standard finite element analysis. Aspects of the application of the method which are particular to induction motors are considered: the means of improving the convergence of the nonlinear finite element equations; the choice of symmetrical sub-domains; the modelling of relative movement; and the inclusion of periodic boundary conditions. © 1999 IEEE.

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In this paper the influence of the form of motor excitation on the performance of a small (< 1 kW) induction motor drive is studied. Two forms of excitation, namely sine waves generated by pulse width modulation and simple square wave are explored. Sine wave excitation gives lower motor losses but increases inverter losses. Conversely, square wave excitation increases motor losses but decreases inverter losses. Losses have been measured directly by calorimetric means or, in the case of the inverter, predicted by a Pspice model that has been verified by calorimetric methods. The work shows that overall, the use of square wave excitation leads to a more efficient drive. © 2004 The Institution of Electrical Engineers.

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Three-phase induction motors offer significant advantages over commutator motors in some domestic appliances. Models for wide speed range three-phase induction motors for use in a horizontal axis washing machine have been developed using the MEGA finite element package with an external formulation for calculating iron losses. Motor loss predictions have been verified using a novel high accuracy calorimeter. Good agreement has been observed over a wide speed range at different loadings. The model is used to predict motor temperature rise under typical washing machine loading conditions to ensure its limiting temperature is not exceeded and enables alternative designs to be investigated without recourse to physical prototypes. © 2005 IEEE.

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This paper presents the results of an investigation into the impact of pulse width modulation (PWM) switching schemes on power losses in induction motors and their inverter drives. The PWM schemes considered include sinusoidal PWM, spacevector PWM and discontinuous PWM. Both experimental results and simulated predictions are presented for fractional horsepower and small integral horsepower motors. Direct loss measurements have been carried out using a calorimetric test rig; detailed simulations of the skewed motors have been carried out using multi-slice time-stepped 2D FEA. The simulated and measured losses under the different modulation schemes are compared and discussed. © 2006 IEEE.

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Adopting square wave excitation to drive induction motors (IMs) can substantially reduce inverter switching losses. However, the low-order time harmonics inherent in the output voltage generates parasitic torques that degrade motor performance and reduce efficiency. In this paper, a novel harmonic elimination modulation technique with full voltage control is studied as an interesting and alternative means of operating small (<1kW) IM drives efficiently. A fully verified harmonic elimination scheme, which removes the 5th, 7th, 11th, 13th and 17 th time harmonics, was implemented and applied to an IGBT driven IM. The power losses incurred in the inverter and the IM as a result of the switching scheme have been determined. © 2008 Crown copyright.

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This paper proposes a movement trajectory planning model, which is a maximum task achievement model in which signal-dependent noise is added to the movement command. In the proposed model, two optimization criteria are combined, maximum task achievement and minimum energy consumption. The proposed model has the feature that the end-point boundary conditions for position, velocity, and acceleration need not be prespecified. Consequently, the method can be applied not only to the simple point-to-point movement, but to any task. In the method in this paper, the hand trajectory is derived by a psychophysical experiment and a numerical experiment for the case in which the target is not stationary, but is a moving region. It is shown that the trajectory predicted from the minimum jerk model or the minimum torque change model differs considerably from the results of the psychophysical experiment. But the trajectory predicted from the maximum task achievement model shows good qualitative agreement with the hand trajectory obtained from the psychophysical experiment. © 2004 Wiley Periodicals, Inc.

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Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models. © 2010 Nagengast et al.

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As we known, the high temperature (77 K) superconducting (HTS) motor is considered as a competitive electrical machine by more and more people. There have been various of designs for HTS motor in the world. However, most of them focus on HTS tapes rather than bulks. Therefore, in order to investigate possibility of HTS bulks on motor application, a HTS magnet synchronous motor which has 75 pieces of YBCO bulks surface mounted on the rotor has been designed and developed in Cambridge University. After pulsed field magnetization (PFM) process, the rotor can trap a 4 poles magnetic field of 375 mT. The magnetized rotor can provide a maximum torque of 49.5 Nm and a maximum power of 7.8 kW at 1500 rpm. © 2010 IEEE.

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This paper presents the results of a study that specifically looks at the relationships between measured user capabilities and product demands in a sample of older and disabled users. An empirical study was conducted with 19 users performing tasks with four consumer products (a clock-radio, a mobile phone, a blender and a vacuum cleaner). The sensory, cognitive and motor capabilities of each user were measured using objective capability tests. The study yielded a rich dataset comprising capability measures, product demands, outcome measures (task times and errors), and subjective ratings of difficulty. Scatter plots were produced showing quantified product demands on user capabilities, together with subjective ratings of difficulty. The results are analysed in terms of the strength of correlations observed taking into account the limitations of the study sample. Directions for future research are also outlined. © 2011 Springer-Verlag.

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For many realistic scenarios, there are multiple factors that affect the clean speech signal. In this work approaches to handling two such factors, speaker and background noise differences, simultaneously are described. A new adaptation scheme is proposed. Here the acoustic models are first adapted to the target speaker via an MLLR transform. This is followed by adaptation to the target noise environment via model-based vector Taylor series (VTS) compensation. These speaker and noise transforms are jointly estimated, using maximum likelihood. Experiments on the AURORA4 task demonstrate that this adaptation scheme provides improved performance over VTS-based noise adaptation. In addition, this framework enables the speech and noise to be factorised, allowing the speaker transform estimated in one noise condition to be successfully used in a different noise condition. © 2011 IEEE.