Online and Offline Rotary Regression Analysis of Torque Estimator for Switched Reluctance Motor Drives

A new torque estimator for switched reluctance motor (SRM) drives based on 2-D rotary regression analysis is presented in this paper. The proposed torque estimator is composed of a bicubic regressive polynomial as a function of rotor position and input current. The regressive coefficients can be computed offline or online from the torque characteristics acquired either experimentally or from numerical computation. Furthermore, a torque estimation method by taking mutual coupling into consideration is proposed. It can be seen that the estimated and experimentally obtained self-coupling and mutual-coupling torque characteristics are in good agreement with each other. In addition, the dynamic torque waveforms with and without the mutual coupling, estimated by the proposed estimator, are found to be virtually the same as those obtained from the bicubic spline interpolation for SRM drives with single-pulse voltage, hysteresis current chopping, as well as with voltage pulse width modulation control. The success of all the case studies being reported is a good validation of the usefulness and accuracy of the proposed real-time torque estimator that, as described in this paper, can be used to quickly estimate the instantaneous output torque of SRM drives.     

Comments on “A New Model of Two Directional Jc Distributions for Bi 2Sr2CaCu2O 8 Materials”

The authors comments on the claim of Takahashi et al. that the distribution model, utilizing the mixture of Gaussian distributions, for the local critical current density of superconducting materials they proposed is a new idea. The authors points out the the method have been known since 1886.     

Entropy of multidimensional cellular automata

Since the topological entropy of a vast class of two-dimensional cellular automata (CA) is infinite, of interest is the possibility to renormalize it so that to obtain a positive finite value. We find the asymptotics of the information function of a multidimensional CA and, accordingly, introduce the renormalized topological entropy as a coefficient of this asymptotics. We describe some properties of the introduced quantity, in particular, its positivity for CA of the type of “The Game of Life.” Also, we give an example of an explicit evaluation of this parameter for a particular cellular automaton.     

Power Distribution Fault Cause Identification With Imbalanced Data Using the Data Mining-Based Fuzzy Classification E-Algorithm

Power distribution systems have been significantly affected by many outage-causing events. Good fault cause identification can help expedite the restoration procedure and improve the system reliability. However, the data imbalance issue in many real-world data sets often degrades the fault cause identification performance. In this paper, the E-algorithm, which is extended from the fuzzy classification algorithm by Ishibuchi to alleviate the effect of imbalanced data constitution, is applied to Duke Energy outage data for distribution fault cause identification. Three major outage causes (tree, animal, and lightning) are used as prototypes. The performance of E-algorithm on real-world imbalanced data is compared with artificial neural network. The results show that the E-algorithm can greatly improve the performance when the data are imbalanced     

Evaluating software reuse alternatives: a model and its application to an industrial case study

We propose a model that enables software developers to systematically evaluate and compare all possible alternative reuse scenarios. The model supports the clear identification of the basic operations involved and associates a cost component with each basic operation in a focused and precise way. The model is a practical tool that assists developers to weigh and evaluate different reuse scenarios, based on accumulated organizational data, and then to decide which option to select in a given situation. The model is currently being used at six different companies for cost-benefit analysis of alternative reuse scenarios; we give a case study that illustrates how it has been used in practice.     

Probability-Theoretic and Statistical Analysis of Dictionary Texts

We consider probability-theoretic and statistical models and methods for computing the characteristics of dictionary structures. Results of a statistical analysis of several commonly used dictionaries are presented in order to test the adequacy of the computing methods proposed.     

Neural-Net Analysis of the Plasticity of ÉP-450 Ferrite–Martensite Steel with Different Alloying Element Concentrations

The results of a computational experiment with a neural-net model simulating the effect of the chemical composition on the plastic properties of ÉP-450 steel are presented. It is shown that computer-aided development of reactor steel with prescribed properties is, in principle, possible.