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Altoona, PA, United States

Comanescu M.,Penn State Altoona
2014 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2014 | Year: 2014

The paper discusses the problem of estimating the speed, the flux magnitude and the rotor flux angle of the induction motor (IM) and presents an estimation method based on two Sliding Mode Observers (SMOs) and the Model Reference Adaptive System (MRAS) technique. The method is based on implementation of two SMOs that both yield the magnitude of the rotor flux; one observer is the reference model, the other is the adjustable model. The MRAS method is used to adapt the speed signal which is an input into both SMOs. The reference model is designed using the equations of the IM in the rotating reference frame. It is shown that its estimated flux magnitude is insensitive to the input speed. The adjustable model uses the IM equations in the stationary reference frame. Its output fluxes have magnitudes inverse proportional with the input speed; however, their phases are always accurate (this allows estimation of the flux angle). Using MRAS, the speed is corrected such that the flux magnitudes coming out of the two models match. Based on the structure developed, the paper also a speed estimation method. The simulations validate the theoretical development. © 2014 IEEE. Source


LaDage L.D.,Penn State Altoona
Integrative and Comparative Biology | Year: 2015

Synopsis Previous to the 1980s, the prevailing neuroscience dogma held that no new neurons were produced in the brains of adult mammals. Now, we understand that the production of new neurons, or neurogenesis, is a common and plastic process in the adult brain. To date, however, researchers have not come to a unified understanding of the functional significance of neurogenesis. Several factors have been shown to modulate hippocampal neurogenesis including spatial learning, stress, and aspects of environmental change, but questions still remain. How do these modulating factors overlap? Which aspects of environmental change induce a stress response? Is there a relationship between hippocampal neurogenesis, the stress response, and environmental change? Can this relationship be altered when taking into consideration other factors such as perception and predictability of the environment? Finally, do results from neurobiological research on laboratory rodents translate to wild systems? This review attempts to address these questions and synthesize research from the fields of ecology, psychology, and behavioral neuroscience. Source


Comanescu M.,Penn State Altoona
Proceedings - ISIE 2011: 2011 IEEE International Symposium on Industrial Electronics | Year: 2011

The paper discusses the problem of integrating the equations of state observers associated with direct field orientation (DFO) of motor drives and studies the influence of the discretization method used on the accuracy of integration. In a typical implementation, discrete-time integration is done using Euler's discretization method (forward rectangular rule) - the method is simple and integration is accurate when the drive operates at low and medium speed. However, as the frequency increases, the integration becomes inaccurate because the Euler approximation starts losing more and more area from under the curve. Theoretically, the problem could be alleviated by increasing the sampling frequency; however, this cannot always be done. Another idea would be to adopt a more accurate (but more computationally intensive) integration method, for example, trapezoidal integration (Tustin method). The paper shows that, at high frequency, under ideal conditions, trapezoidal integration performs better than the Euler method. In a real implementation, however, conditions are non-ideal since the measured signals bring dc offsets and imperfections into the terms to be integrated - as a result, pure integration must be replaced with quasi-low pass filtering. Under these conditions, the paper compares the Euler, Tustin and backward rectangular methods from the point of view of integration accuracy. The implications related to direct field orientation of motor drives are studied by considering a full-order observer for the PMSM - this is discretized using the three methods considered and the results are compared. At high frequency, neither integration method gives perfect results; the Euler method yields a waveform that leads the expected one while the backward rectangular method yield a waveforms that lags it. The paper finds that, surprisingly, when quasi-low pass filtering is used, the Tustin method is not significantly more accurate than the other ones - the waveform obtained lags the expected one by an angle comparable with the lead angle of the Euler method. It is shown that the integration accuracy depends on the frequency, sampling time, filter bandwidth and on the integration method used. Accurate high frequency drive DFO control would require correction of the magnitude/phase of the estimates. © 2011 IEEE. Source


Comanescu M.,Penn State Altoona
IECON Proceedings (Industrial Electronics Conference) | Year: 2012

The paper discusses the problem of sensorless rotor flux angle/rotor position estimation for the permanent magnet synchronous motor (PMSM) and for the induction motor (IM) and presents a family of sensorless observer designs that use a speed estimate. In sensorless AC drive control, it is typical to measure the motor's voltages and currents and to estimate the other quantities of interest: speed, fluxes (EMFs) and rotor position. The simultaneous estimation of these quantities is possible, however, the methods available are rather complicated and the accuracy is often questionable, especially under parameter variations. The paper proposes a sequential approach which is simpler: first, estimate the drive's speed; then, use this speed estimate along with the measurements to estimate the states of the motor model and to obtain the field orientation angle. A family of observers for the IM and the PMSM is presented - these are constructed using their models in the stationary reference frame. The observers are developed assuming that the speed estimate obtained is different from the real speed; it is shown that despite this inaccuracy, with special gain designs, the correct field orientation angle is obtained. The observers are developed using Sliding Mode and/or Lyapunov methods. They can be directly applied in sensorless field-oriented drives that do not require the magnitude of the flux. © 2012 IEEE. Source


Emili L.A.,Penn State Altoona | Greene R.P.,Northern Illinois University
Environmental Management | Year: 2013

Agricultural non-point source (NPS) pollution, primarily sediment and nutrients, is the leading source of water-quality impacts to surface waters in North America. The overall goal of this study was to develop geographic information system (GIS) protocols to facilitate the spatial and temporal modeling of changes in soils, hydrology, and land-cover change at the watershed scale. In the first part of this article, we describe the use of GIS to spatially integrate watershed scale data on soil erodibility, land use, and runoff for the assessment of potential source areas within an intensively agricultural watershed. The agricultural non-point source pollution (AGNPS) model was used in the Muddy Creek, Ontario, watershed to evaluate the effectiveness of management strategies in decreasing sediment and nutrient [phosphorus (P)] pollution. This analysis was accompanied by the measurement of water-quality parameters (dissolved oxygen, pH, hardness, alkalinity, and turbidity) as well as sediment and P loadings to the creek. Practices aimed at increasing year-round soil cover would be most effective in decreasing sediment and P losses in this watershed. In the second part of this article, we describe a method for characterizing land-cover change in a dynamic urban fringe watershed. The GIS method we developed for the Blackberry Creek, Illinois, watershed will allow us to better account for temporal changes in land use, specifically corn and soybean cover, on an annual basis and to improve on the modeling of watershed processes shown for the Muddy Creek watershed. Our model can be used at different levels of planning with minimal data preprocessing, easily accessible data, and adjustable output scales. © 2012 Springer Science+Business Media, LLC. Source

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