Switched reluctance motor modeling with on-line parameteridentification

A nonlinear model with on-line parameter estimation using recursive identification for switched reluctance motors (SRMs) is presented. The model is robust toward parameter variations in the motor or any system disturbances. The parameters of the model are adjusted to account for errors in rotor position, which allows the use of crude inexpensive position sensors. The proposed modeling approach allows self-tuning of SRMs in a production unit. The simulations and experiments performed to test the model demonstrate the accuracy of estimation of the model     

Fractional wavelet transform for the quantitative spectral resolution of the composite signals of the active compounds in a two-component mixture

Fractional calculus is a powerful tool that has been applied successfully for the analysis of the complex systems. One interesting example of a complex mixture is given by the multicomponent pharmaceutical samples having constant matrix content. The main aim of this study is to develop a new approach based on the combined use of the fractional wavelet transform (FWT) and the continuous wavelet transform (CWT) in order to quantify atorvastatin (ATO) and amlodipine (AML) in their mixtures without requiring a chemical pretreatment. In the first step, the absorption spectra of the compounds and their samples were processed by the FWT method. In the next step, the CWT approach was applied to the fractional wavelet spectra obtained in the above step. The aim of the application of FWT is data reduction corresponding to the spectra of compounds and their commercial samples. In the following step, the CWT was used for the quantitative resolution of the composite signals of the analyzed compounds. After method validation, the proposed signal processing methods based on the combined use of the FWT and the CWT were successfully applied to the resolution of the composite spectra for the quantitation of atorvastatin (ATO) and amlodipine (AML) in tablets.     

Design, fabrication and control of a magnetic capsule-robot for the human esophagus

Much research on the development of a robotic capsule and micro robot for the diagnosis of gastrointestinal diseases has been carried out. The powering of these micro systems is becoming very challenging as the implementation of such systems is limited due to the existence of on-board power supplies. This paper presents a micro robotic system based on magnetic principles. The goal is to build a system in which a capsule-robot can be manipulated wirelessly inside an enclosed environment such as human??s body. A prototype of capsule-robot is built and tested, that can be remotely operated with three DOF in an enclosed environment by transferring magnetic energy and electromagnetic waves. A magnetic drive unit generates magnetic energy for the manipulation. Experimental results show the capsule-robot is manipulated and moved through a desired trajectory in a viscous fluid. The capsule-robot can be potentially used for endoscopy and colonoscopy.     

A new expert system for learning management systems evaluation based on neutrosophic sets

There has been a sudden increase in the usage of Learning Management Systems applications to support learner's learning process in higher education. Many studies in learning management system evaluation are implemented under complete information, while the real environment has uncertainty aspects. As these systems were described by development organizations with uncertainty terms such as vague, imprecise, ambiguity and inconsistent, that is why traditional evaluation methods may not be effective. This paper suggests neutrosophic logic as a better option to simulate human thinking than fuzzy logic because unlike fuzzy logic, it is able to handle indeterminacy of information which expresses the percentage of unknown parameters. As previous studies suggested neutrosophic decision maker and neutrosophic expert systems as future work in ecommerce and e‐learning applications, this paper presents neutrosphic expert system for learning management systems evaluation. Information for building and validating the neutrosophic expert system is collected from five experts using surveys, and then analysis is done by using Fuzzytech 5.54d software. Finally, the comparison between fuzzy expert system and neutrosophic expert system results show that the neutrosophic logic is capable of representing uncertainty in human thinking for evaluating Learning Management Systems.     

Ferrimagnetic resonance and low temperature transition in Ni- and Co-substituted powder magnetite

The effects of nickel and cobalt substitution on ferrimagnetic resonance in high-purity magnetite powder have been investigated. The low-temperature transition temperature and damping parameter, , are found to decrease with increasing solute additions. The linewidth, H, varies in proportion to the anisotropy field of the ferrites, narrowing with increasing nickel content but broadening with increasing cobalt content. Theg factor increases with the dopant concentration, passing through a maximum around room temperature. Decreasing the deviation from stoichiometry by appropriate annealing decreases the transition temperature shift but slightly increases H, g and .     

Dynamic hierarchical bandwidth allocation using Russian Doll Model in EPON

This paper demonstrates a new hierarchical Dynamic Bandwidth Allocation algorithm using the Russian Doll Model (RDM) to allocate bandwidth for intra-Optical Network Unit (ONU) in an Ethernet Passive Optical Network (EPON). The allocation of bandwidth is based on the classification and prioritization of service. The algorithm addresses the requests of ONUs and provides differentiated services by balancing priority and fairness. The simulation results show that the proposed algorithm performs well in supporting the triple-play services, i.e. video, voice, and data, as well as making effective adjustment in balancing bandwidth sharing between the ONUs compared with two other existing Dynamic Bandwidth Allocation (DBA) algorithm. The proposed algorithms shows significant performance improvements in terms of bandwidth utilization, packet delay and the fairness.     

Sequence-dependent group scheduling problem on unrelated-parallel machines

In this research we address a sequence-dependent group scheduling problem on a set of unrelated-parallel machines where the run time of each job differs on different machines. To benefit both producer and customers we attempt to minimize a linear combination of total weighted completion time and total weighted tardiness. Since the problem is shown to be NP-hard, meta-heuristic algorithms based on tabu search are developed to find the optimal/near optimal solution. For some small size yet complex problems, the results from these algorithms are compared to the optimal solutions found by CPLEX. The result obtained in all of these problems is that the tabu search algorithms could find solutions at least as good as CPLEX but in drastically shorter computational time, thus signifying the high degree of efficiency and efficacy attained by the former.     

可控串补在天平500kV交流输变电工程中的应用

通过对天平500kV线路可控串补系统控制及保护模块的介绍,剖析了该可控串补系统固定式常规串补(FSC)和动态式可控串补(TCSC)的控制和触发过程及保护原理,强调随着可控硅、氧化锌非线性电阻等先进技术的研发和应用,串补技术在电网系统尤其是超高压远距离输电系统中的应用前景广阔。