Sharif Digital Repository

This paper describes a novel Direct Torque Control (DTC) method for adjustable speed Doubly-Fed Induction Machine (DFIM) drives which is supplied by a two-level Space Vector Modulation (SVM) voltage source inverter (DTC-SVM) in the rotor circuit. The inverter reference voltage vector is obtained by using input-output feedback linearization control and a DFIM model in the stator a-b axes reference frame with stator currents and rotor fluxes as state variables. Moreover, to make this nonlinear controller stable and robust to most varying electrical parameter uncertainties, a two layer recurrent Artificial Neural Network (ANN) is used to estimate a certain function which shows the machine... 

In this paper, a decentralized controller for trajectory tracking of modular and reconfigurable robot manipulators is developed. The proposed control scheme uses joint-torque sensory feedback; also sliding mode control is employed to make both position and velocity tracking errors of robot manipulators globally converging to zero. Proposed scheme also guarantees that all signals in closed-loop systems will be bounded. In contrast to some of prior works in this scheme, each controller uses a smooth law to achieve its purposes. In this method, each controller uses only local information for producing control law hence separated controller can be used to control each module of manipulator and... 

The most important disadvantage of swinging interferometers is that the optical path difference created in them is a nonlinear function of the rotation angle. In this paper, two new swinging interferometers are presented which have good linearity and provide a larger path difference in response to the rotation angle compared to other interferometers. This makes them suitable for applications such as high-resolution spectroscopy, and precision micro and nanopositioning. In one of these two interferometers, the optical path difference is created by rotation of a system composed of four mirrors, and in the other one it is created by rotation of a system consisting of two mirrors. They are not... 

Palm oil (PO) and sunflower oil (SFO) blends with varying proportions were subjected to enzymatic interesterification (EIE) using a 1,3-specific immobilised lipase. The interesterified blends were evaluated for their slip melting point (SMP), solid fat content (SFC) at 10-40°C, p-anisidine value, peroxide value, free fatty acids (FFA), induction period of oxidation at 110°C (IP110) and composition of fatty acids by gas chromatography. Under EIE treatment, the blends of PO and SFO in different proportions (20:80, 40:60, 50:50, 60:40 and 80:20) had saturated and unsaturated fatty acid content in the range of 37.6-52.0% and 48.0-62.4%, respectively. The blends showed a considerable reduction in... 

Conjugated Linoleic Acid (CLA), Glycerol (G) and sunflower oil blends with varying concentration were subjected to enzymatic esterification using a 1, 3-specific immobilized lipase. CLA was used as acyl due to its purported health benefits. The transesterified lipids were evaluated for free fatty acids (FFA) and composition of fatty acids by gas chromatography. Lipozyme RM IM is preferred for enzymatic esterification because of more CLA incorporation and less free fatty acids at the end of reaction than Lipozyme TL IM. Response surface methodology (RSM) was used to determine the effects of three variables Glycerol concentration, reaction temperature, and amount of enzyme on the lipase... 

Rolling-element bearing (REB) failure is one of the general damages in rotating machinery. In this manner, the correct prediction of remaining useful life (RUL) of REB is a crucial challenge to move forward the unwavering quality of the machines. One of the main difficulties in implementing data-driven methods for RUL prediction is to choose proper features that represent real damage progression. In this article, by using the outcomes of frequency analysis through the Envelope method, the initiated/existed defects on the ball bearings are identified. Also, new features based on developing faults of ball bearings is recommended to estimate RUL. Early-stage faults in ball bearings usually... 

The biped walking robot demonstrates a stable limit cycle on shallow slopes. In previous researches, this passive gait was shown to be sensitive to ground slope and initial conditions. In this paper, we discuss the feedback stabilization of a biped robot by the "energy shaping" technique. Two designs are proposed to reduce the sensitivity of the biped walking robot to slope and initial conditions. In the first design, a moving mass actuator is located on each link of the robot. The actuators are used to shape the potential energy of the biped robot so that it tracks the potential energy of a known passive gait of a similar biped robot on a different slope. Although the method is applied to a... 

The spatiotemporal dynamic of salinity concentration (SC) in saline lakes is strongly dependent on the rate of water flow into the lake, water circulation, wind speed, evaporation rate, and the phenomenon of salt precipitation and dissolution. Although in-situ observations most reliably quantify water quality metrics, the spatiotemporal distribution of such data are typically limited and cannot be readily extrapolated for either long-term projections or extensive areas. Alternatively, remotely sensed imagery has facilitated less expensive and a stronger ability to estimate water quality over a wide range of spatiotemporal resolutions. This study introduces an adaptive learning model that... 

The interaction between a lake and groundwater has important implications to the quantity and quality of water in both environments. Quantification of lake-groundwater interaction (LGI) has been challenging in regions with limited in-situ data. LGI can be quantified by physically-based models, direct measurement of seepage, measurements of conservative chemical or isotopic tracers, and lake water balance. Despite the accuracy of the methods based on hydrochemical or isotopic measurements and analysis, they require extensive field data that are costly to collect in large lakes. Instead, the data required to quantify LGI by the lake water budget method can be obtained via typical ground... 

The rapid shrinkage of Lake Urmia over the past two decades has raised serious environmental concerns. Several restoration plans have been proposed to reduce agricultural water consumption to supply a remarkable fraction of the lake's environmental flow requirement. However, an accurate and realistic evaluation of the effectiveness of these plans in reducing agricultural water consumption across the basin is still poorly understood. This study assessed the water-saving potential of agricultural alteration in a snow-dominated catchment in the Lake Urmia Basin. In particular, we explored the impact of crop pattern alteration via reducing the cultivation area and employing different irrigation... 

Oil spill is the main cause of marine pollution in the waterbodies with rich oil resources. In this study, we developed and compared the performance of variable-complexity machine-learning models to detect oil spill origin, extent, and movement over large scales. To this end, we trained Support Vector Machine (SVM), Random Forest (RF), and Convolutional Neural Network (CNN) models by using the statistical, geometrical, and textural features of Sentinel-1 SAR data. Our results in the Persian Gulf showed that CNN is superior to RF and SVM classifiers in oil spill detection, as evidenced by the testing accuracy of 95.8 %, 86.0 %, and 78.9 %, respectively. The results suggested utilizing both... 

Gorgan Bay (GB) and Miankaleh Peninsula biosphere reserve has faced an endangering condition because of a significant water loss and quality degradation due to intensive eutrophication. However, a synoptic view of the spatiotemporal dynamic of eutrophication is missing. In this study, we first used MODIS data to trace the long-term trend of eutrophication in GB between 2003 and 2021. To investigate the intra-annual variability of Chl-a in GB at a much higher spatial resolution, we developed an Artificial Neural Network (ANN) algorithm that uses Sentinel-2 imagery to map monthly Chl-a in the water year 2020–2021. Finally, we explored the major physical controls on eutrophication in GB....