فهرست مطالب s. sadr

Linear Induction Motors (LIMs) are favorite machines utilized in various industrial applications. But, due to the end effect phenomena, control of a LIM drive is more complicated than rotational machine drives. Therefore, selecting the proper control strategy for a LIM drive has been a significant challenge for the researchers. This paper concentrates on a new Model Predictive Control (MPC) of LIM drives which considers the end effect.Accordingly, the discrete-time model of the LIM with end effect is extracted, and the required flowchart used for the MPC of LIM drive has been presented in this paper. To study the effectiveness of the suggested strategy, simulation results of a LIM drive with MPC are presented and compared to the traditional Indirect Field Oriented Control (IFOC) of LIM drive. Simulations have been carried out using Matlab. The end effect has been considered in the LIM model and control strategies. Simulation results validate that the suggested MPC of LIM drive yields excellent dynamic characteristics such as fast speed response with no overshoot. Moreover, in comparison to the traditional IFOC method, the suggested MPC strategy offers lower current ripple and lower electromagnetic force ripple, and therefore, it is suitable for industrial drive applications.

Soil compactibility can be quantified using different indices such as maximum dry bulk density (BDmax) and critical water content (θcritical) in a compaction test. The objective of this study was to determine soil properties influencing soil compactibility by evaluate pedotranfer functions (PTFs) with respect to their accuracy and usefulness for the prediction of BDmax and θcritical using linear regression and ANN methods. 100 soil samples were collected from arable and virgin lands in southeast Iran. Primary particle size distribution, CaSO4, CaCO3, organic matter (OM) contents and natural bulk density were used as predictors. Two PTFs were developed using linear multiple stepwise regression: a PTF that estimates BDmax using clay and sand contents and natural bulk density as predictors (R2 = 0.45), the other one for the estimation of θcritical using clay and CaSO4 contents as predictors (R2 = 0.51). Furthermore, an attempt was made to construct PTFs for the prediction of the BDmax and θcritical using ANNs. High prediction efficiencies were achieved using the ANN models. Generally, when all of the easily-available soil properties were included as predictors, much more accurate estimates were obtained by the ANN models for the θcritical and BDmax as compared with the linear regression method. Sensitivity analysis showed that the most important variable in BDmax prediction using ANNs is the BDnatural followed by sand and clay, CaCO3 and CaSO4 contents. The θcritical had the highest sensitivity to clay content and the lowest sensitivity to OM content in the studied soils.

The principal aim of this paper is to show an independent vector control of two five-phase Linear Induction Motors (LIMs) that are supplied from a single VSI. The LIMs are running at the same speed but with different load conditions. This concept can be especially beneficial in long trains with distributed power. To achieve excellent control characteristics and to reduce the undesirable tension forces between the train mechanical couplers, Fuzzy Logic Controllers (FLCs) have been utilized. As a result, the fault occurrence of the train control systems decreases, and the system reliability increases. The results prove the electrical independence in control of a five-phase two-LIM drive supplied with a single VSI. Furthermore, in the presence of the train mechanical couplers and connections, the application of FLC offers excellent control characteristics and reduces the undesirable tension forces. Furthermore, to obtain a more worthwhile validation of the theoretical results, an experimental set up has been constructed and results have also been presented. According to the results, the undesirable tension forces imposed on train couplers are reduced. Consequently, it leads to higher system efficiency, lower deterioration of the train couplers and connections, greater system reliability, and higher passenger safety and comfort.