Search results for: M. O. Tokhi
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3

Search results for: M. O. Tokhi

3 Control of Single Axis Magnetic Levitation System Using Fuzzy Logic Control

Authors: A. M. Benomair, M. O. Tokhi

Abstract:

This paper presents the investigation on a system model for the stabilization of a Magnetic Levitation System (Maglev’s). The magnetic levitation system is a challenging nonlinear mechatronic system in which an electromagnetic force is required to suspend an object (metal sphere) in air space. The electromagnetic force is very sensitive to the noise which can create acceleration forces on the metal sphere, causing the sphere to move into the unbalanced region. Maglev’s give the contribution in industry and this system has reduce the power consumption, has increase the power efficiency and reduce the cost maintenance. The common applications for Maglev’s Power Generation (e.g. wind turbine), Maglev’s trains and Medical Device (e.g. Magnetically suspended Artificial Heart Pump). This paper presents the comparison between dynamic response and robust characteristic for both conventional PD and Fuzzy PD controller. The main contribution of this paper is the proof of fuzzy PD type stabilization and robustness. By use of a method to tune the scaling factors of the linear PD type fuzzy controller from an equivalent tuned conventional PD.

Keywords: magnetic levitation system, PD controller, Fuzzy Logic Control, Fuzzy PD

Procedia PDF Downloads 245
2 Land Suitability Assessment for Vineyards in Afghanistan Based on Physical and Socio-Economic Criteria

Authors: Sara Tokhi Arab, Tariq Salari, Ryozo Noguchi, Tofael Ahamed

Abstract:

Land suitability analysis is essential for table grape cultivation in order to increase its production and productivity under the dry condition of Afghanistan. In this context, the main aim of this paper was to determine the suitable locations for vineyards based on satellite remote sensing and GIS (geographical information system) in Kabul Province of Afghanistan. The Landsat8 OLI (operational land imager) and thermal infrared sensor (TIRS) and shuttle radar topography mission digital elevation model (SRTM DEM) images were processed to obtain the normalized difference vegetation index (NDVI), normalized difference moisture index (NDMI), land surface temperature (LST), and topographic criteria (elevation, aspect, and slope). Moreover, Jaxa rainfall (mm per hour), soil properties information are also used for the physical suitability of vineyards. Besides, socio-economic criteria were collected through field surveys from Kabul Province in order to develop the socio-economic suitability map. Finally, the suitable classes were determined using weighted overly based on a reclassification of each criterion based on AHP (Analytical Hierarchy Process) weights. The results indicated that only 11.1% of areas were highly suitable, 24.8% were moderately suitable, 35.7% were marginally suitable and 28.4% were not physically suitable for grapes production. However, 15.7% were highly suitable, 17.6% were moderately suitable, 28.4% were marginally suitable and 38.3% were not socio-economically suitable for table grapes production in Kabul Province. This research could help decision-makers, growers, and other stakeholders with conducting precise land assessments by identifying the main limiting factors for the production of table grapes management and able to increase land productivity more precisely.

Keywords: vineyards, land physical suitability, socio-economic suitability, AHP

Procedia PDF Downloads 136
1 Yield Loss Estimation Using Multiple Drought Severity Indices

Authors: Sara Tokhi Arab, Rozo Noguchi, Tofeal Ahamed

Abstract:

Drought is a natural disaster that occurs in a region due to a lack of precipitation and high temperatures over a continuous period or in a single season as a consequence of climate change. Precipitation deficits and prolonged high temperatures mostly affect the agricultural sector, water resources, socioeconomics, and the environment. Consequently, it causes agricultural product loss, food shortage, famines, migration, and natural resources degradation in a region. Agriculture is the first sector affected by drought. Therefore, it is important to develop an agricultural drought risk and loss assessment to mitigate the drought impact in the agriculture sector. In this context, the main purpose of this study was to assess yield loss using composite drought indices in the drought-affected vineyards. In this study, the CDI was developed for the years 2016 to 2020 by comprising five indices: the vegetation condition index (VCI), temperature condition index (TCI), deviation of NDVI from the long-term mean (NDVI DEV), normalized difference moisture index (NDMI) and precipitation condition index (PCI). Moreover, the quantitative principal component analysis (PCA) approach was used to assign a weight for each input parameter, and then the weights of all the indices were combined into one composite drought index. Finally, Bayesian regularized artificial neural networks (BRANNs) were used to evaluate the yield variation in each affected vineyard. The composite drought index result indicated the moderate to severe droughts were observed across the Kabul Province during 2016 and 2018. Moreover, the results showed that there was no vineyard in extreme drought conditions. Therefore, we only considered the severe and moderated condition. According to the BRANNs results R=0.87 and R=0.94 in severe drought conditions for the years of 2016 and 2018 and the R= 0.85 and R=0.91 in moderate drought conditions for the years of 2016 and 2018, respectively. In the Kabul Province within the two years drought periods, there was a significate deficit in the vineyards. According to the findings, 2018 had the highest rate of loss almost -7 ton/ha. However, in 2016 the loss rates were about – 1.2 ton/ha. This research will support stakeholders to identify drought affect vineyards and support farmers during severe drought.

Keywords: grapes, composite drought index, yield loss, satellite remote sensing

Procedia PDF Downloads 114