Sensorless speed measurement using current harmonic spectralestimation in induction machine drives

This paper proposes a sensorless speed measurement scheme that improves the performance of transducerless induction machine drives, especially for low-frequency operation. Speed-related harmonics that arise from rotor slotting and eccentricity are analyzed using digital signal processing. These current harmonics exist at any nonzero speed and are independent of time-varying parameters, such as stator winding resistance. A spectral estimation technique combines multiple current harmonics to determine the rotor speed with more accuracy and less sensitivity to noise than analog filtering methods or the fast Fourier transform. An on-line initialization routine determines machine-specific parameters required for slot harmonic calculations. This speed detector, which has been verified at frequencies as low as 1 Hz, can provide robust, parameter-independent information for parameter tuning or as an input to a sensorless flux observer for a field-oriented drive. The performance of the algorithm is demonstrated over a wide range of inverter frequencies and load conditions     

Semi-wet growth and characterization of multi-functional nano-engineered mixed metal oxides for industrial application

This review paper covers the low temperature wet growth of nano-engineered particles of ZnO-based mixed metal oxides, their growth mechanism, and characterization using X-ray diffraction, SEM, TEM and IR, UV–visible, and XPS spectral techniques. Main focus of this article is centered on low temperature semi-wet methods of synthesis that are suitable for large scale production of zinc oxide-based systems mixed with iron oxide, copper oxide, nickel oxide and cobalt oxide. These mixed metal oxides have broad industrial applications as catalyst, semiconductors, adsorbents, superconductors, electro-ceramics, and antifungal agents in addition to extensive applications in medicines. This paper discusses the low-cost and environment friendly synthesis of these mixed metal oxides, measurement of properties and applicability of these materials systems.     

Acoustic noise reduction in sinusoidal PWM drives using a randomlymodulated carrier

Acoustic noise in an inverter-driven electric machine can be reduced by avoiding the concentration of harmonic energy in distinct tones. One method to spread out the harmonic spectrum without the use of programmed PWM (pulse width modulation) is to make the switching pattern random. It is proposed that the switching pattern can be randomized by modulating the triangle carrier in sinusoidal PWM with bandlimited white noise. All of the advantages of sinusoidal PWM are preserved with this technique. These include, real-time control, linear operation, good transient response, and a constant average switching frequency. By controlling the bandwidth and RMS value of the bandwidth limited noise modulation, it is shown that the instantaneous variation in switching frequency and the bandwidth of the energy spectrum in the machine can be specified within predetermined limits. Experimental results show the absence of acoustic noise concentrated at specific tones, which is present in conventional sinusoidal modulation     

Global stability of a two-species piecewise linear volterra ecosystem

This paper extends the results of Goh [1], and Takeuchi and Adachi [2,3] concerning the generalized linear Volterra model. We introduce a piecewise linear Volterra model for a two- species system. The solution of the steady-state problem is then shown to be equivalent to finding the solution to the Generalized Linear Complementarity Problem. We show when this nonnegative equilibrium is unique and globally asymptotically stable in the sense of Goh [1].     

A Model Reduction Perspective on Thermal Models for Induction Machine Overload Relays

Full-order thermal models are often used by machine designers to analyze the induction machine thermal behavior. The real-time implementation of such models for the purpose of motor thermal protection is difficult because an extensive knowledge on motors and sufficient computational resource are required. This paper demonstrates that full-order thermal models can be systematically reduced via pole-zero cancellation or Hankel singular-values-based model reduction techniques without additional physical assumptions. As a result, a system of a substantially lower dimension, which has nearly the same response characteristics in the frequency band of interest, is obtained. Both the estimated rotor cage temperature, which is extracted from the voltage and current measurements by a sensorless rotor temperature estimator, and the measured stator winding temperature are used to evaluate the performance of low-order thermal models. Given a certain tolerance for the modeling error, a reduced low-order thermal model can be used to characterize the thermal dynamics of a small- to medium-sized line-connected induction machine and to provide proper protection against motor overheating.     

Spherically symmetric inhomogeneous dust collapse in higher dimensional space-time and cosmic censorship hypothesis

We consider a collapsing spherically symmetric inhomogeneous dust cloud in higher dimensional space-time. We show that the central singularity of collapse can be a strong curvature or a weak curvature naked singularity depending on the initial density distribution.     

Synaptic depression and short-term habituation are located in the sensory part of the mammalian startle pathway

Background  

Short-term habituation of the startle response represents an elementary form of learning in mammals. The underlying mechanism is located within the primary startle pathway, presumably at sensory synapses on giant neurons in the caudal pontine reticular nucleus (PnC). Short trains of action potentials in sensory afferent fibers induce depression of synaptic responses in PnC giant neurons, a phenomenon that has been proposed to be the cellular correlate for short-term habituation. We address here the question whether both this synaptic depression and the short-term habituation of the startle response are localized at the presynaptic terminals of sensory afferents. If this is confirmed, it would imply that these processes take place prior to multimodal signal integration, rather than occurring at postsynaptic sites on PnC giant neurons that directly drive motor neurons.     

Combined deadbeat control of a series-parallel convertercombination used as a universal power filter

This paper presents the notion of combined control of a system of interconnected power electronic converters. The concept is demonstrated using a three-phase series-parallel active power filter as an example. The described active power filter consists of a series-parallel combination of two full bridge VSIs capable of arbitrarily controlling the input current and output voltage. The proposed control scheme treats the converter combination as a single unit and uses the inverse system model to generate deadbeat control response for both input current and output voltage. A full-order predictive state observer is used to reduce the number of sensors. Simulation results show better disturbance rejection characteristics of the proposed control when compared to the separately controlled converter scheme     

Stator resistance tuning in a stator-flux field-oriented driveusing an instantaneous hybrid flux estimator

A self-tuning control scheme for stator-flux field-oriented induction machine drives in electric vehicles operating over a wide speed range is discussed in this paper. The stator flux can be determined accurately from the terminal voltage when the machine is operating at high speed. However, at low speed, the stator resistance must be known to calculate the stator flux. The problem of calculating the stator flux accurately over the entire speed range is addressed. The rotor flux can be found from the machine speed and rotor time constant. The stator flux, at low speed, is then calculated directly from the rotor flux. By alternating between these two methods of determining the stator flux, a self-tuning operation is achieved, wherein the stator and rotor resistances are periodically updated. Since both methods of determining the stator flux are forced to track one another, a smooth transition between flux estimators is obtained. The torque and flux are then controlled in a deadbeat fashion. Good torque control over a wide speed range can therefore be obtained. With the proposed scheme, the advantages of direct torque control are obtained over the entire speed range with the addition of a speed sensor     

A fast on-line neural-network training algorithm for a rectifierregulator

This paper addresses the problem of deadbeat control in fully controlled high-power factor rectifiers. Improved deadbeat control can be achieved through the use of neural network-based predictors for the input current reference to the rectifier. In this application, online training is absolutely required. In order to achieve sufficiently fast online training, a new random search algorithm is presented and evaluated. Simulation results show that this type of network training yields equivalent performance to standard backpropagation training. Unlike backpropagation, however, the random weight change method can be implemented in mixed digital/analog hardware for this application. The paper proposes a very large-scale integration implementation which achieves a training epoch as low as 8 μs