The Experts below are selected from a list of 196767 Experts worldwide ranked by ideXlab platform
Fayez F M Elsousy - One of the best experts on this subject based on the ideXlab platform.
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self organizing recurrent fuzzy wavelet neural network based mixed rm h _ 2 rm h _ rm infty adaptive tracking control for uncertain two axis motion control system
IEEE Transactions on Industry Applications, 2016Co-Authors: Fayez F M Elsousy, Khaled A AbuhaselAbstract:In this paper, an intelligent adaptive tracking control system (IATCS) based on the mixed $H_{2}/ H_{\rm{\infty }}$ approach for achieving high Precision Performance of a two-axis motion control system is proposed. The two-axis motion control system is an X-Y table driven by two permanent-magnet linear synchronous motors (PMLSMs) servo drives. The proposed control scheme incorporates a mixed $H_{2}/ H_{\rm{\infty }}$ controller, a self-organizing recurrent fuzzy-wavelet-neural-network controller (SORFWNNC), and a robust controller. The SORFWNNC is used as the main tracking controller to adaptively estimate an unknown nonlinear dynamic function (UNDF) that includes the lumped parameter uncertainties, external disturbances, cross-coupled interference, and frictional force. Furthermore, a robust controller is designed to deal with the approximation error, optimal parameter vectors, and higher order terms in Taylor series. Besides, the mixed $H_{2}/ H_{\rm{\infty }}$ controller is designed such that the quadratic cost function is minimized and the worst case effect of the UNDF on the tracking error must be attenuated below a desired attenuation level. The online adaptive control laws are derived based on Lyapunov theorem and the mixed $H_{2}/ H_{\rm{\infty }}$ tracking Performance so that the stability of the IATCS can be guaranteed. The experimental results confirm that the proposed IATCS grants robust Performance and precise dynamic response to the reference contours regardless of external disturbances and parameter uncertainties.
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intelligent mixed h 2 h adaptive tracking control system design using self organizing recurrent fuzzy wavelet neural network for uncertain two axis motion control system
Applied Soft Computing, 2016Co-Authors: Fayez F M ElsousyAbstract:Abstract In this paper, an intelligent adaptive tracking control system (IATCS) based on the mixed H2/H∞ approach under uncertain plant parameters and external disturbances for achieving high Precision Performance of a two-axis motion control system is proposed. The two-axis motion control system is an X–Y table driven by two permanent-magnet linear synchronous motors (PMLSMs) servo drives. The proposed control scheme incorporates a mixed H2/H∞ controller, a self-organizing recurrent fuzzy-wavelet-neural-network controller (SORFWNNC) and a robust controller. The combinations of these control methods would insure the stability, robustness, optimality, overcome the uncertainties, and Performance properties of the two-axis motion control system. The SORFWNNC is used as the main tracking controller to adaptively estimate an unknown nonlinear dynamic function that includes the lumped parameter uncertainties, external disturbances, cross-coupled interference and frictional force. Moreover, the structure and the parameter learning phases of the SORFWNNC are performed concurrently and online. Furthermore, a robust controller is designed to deal with the uncertainties, including the approximation error, optimal parameter vectors and higher order terms in Taylor series. Besides, the mixed H2/H∞ controller is designed such that the quadratic cost function is minimized and the worst case effect of the unknown nonlinear dynamic function on the tracking error must be attenuated below a desired attenuation level. The mixed H2/H∞ control design has the advantage of both H2 optimal control Performance and H∞ robust control Performance. The sufficient conditions are developed for the adaptive mixed H2/H∞ tracking problem in terms of a pair of coupled algebraic equations instead of coupled nonlinear differential equations. The coupled algebraic equations can be solved analytically . The online adaptive control laws are derived based on Lyapunov theorem and the mixed H2/H∞ tracking Performance so that the stability of the proposed IATCS can be guaranteed. Furthermore, the control algorithms are implemented in a DSP-based control computer. From the experimental results, the motions at X-axis and Y-axis are controlled separately, and the dynamic behaviors of the proposed IATCS can achieve favorable tracking Performance and are robust to parameter uncertainties.
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self organizing recurrent fuzzy wavelet neural network based mixed h2 h adaptive tracking control for uncertain two axis motion control system
IEEE Industry Applications Society Annual Meeting, 2015Co-Authors: Fayez F M Elsousy, Khaled A AbuhaselAbstract:In this paper, an intelligent adaptive tracking control system (IATCS) based on the mixed Jf2AC approach for achieving high Precision Performance of a two-axis motion control system is proposed. The two-axis motion control system is an X-Y table driven by two permanent-magnet linear synchronous motors (PMLSMs) servo drives. The proposed control scheme incorporates a mixed H2/H∞ controller, a self-organizing recurrent fuzzy-wavelet-neural-network controller (SORFWNNC) and a robust controller. The SORFWNNC is used as the main tracking controller to adaptively estimate an unknown nonlinear dynamic function (UNDF) that includes the lumped parameter uncertainties, external disturbances, cross-coupled interference and frictional force. Furthermore, a robust controller is designed to deal with the approximation error, optimal parameter vectors and higher order terms in Taylor series. Besides, the mixed H2/H∞ controller is designed such that the quadratic cost function is minimized and the worst case effect of the UNDF on the tracking error must be attenuated below a desired attenuation level. The online adaptive control laws are derived based on Lyapunov theorem and the mixed H2/H∞, tracking Performance so that the stability of the IATCS can be guaranteed. The experimental results confirm that the proposed IATCS grants robust Performance and precise dynamic response to the reference contours regardless of external disturbances and parameter uncertainties.
Kimberly A Novick - One of the best experts on this subject based on the ideXlab platform.
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water vapor δ 2 h δ 18 o and δ 17 o measurements using an off axis integrated cavity output spectrometer sensitivity to water vapor concentration delta value and averaging time
Rapid Communications in Mass Spectrometry, 2016Co-Authors: Chao Tian, Lixin Wang, Kimberly A NovickAbstract:RATIONALE High-Precision analysis of atmospheric water vapor isotope compositions, especially δ(17) O values, can be used to improve our understanding of multiple hydrological and meteorological processes (e.g., differentiate equilibrium or kinetic fractionation). This study focused on assessing, for the first time, how the accuracy and Precision of vapor δ(17) O laser spectroscopy measurements depend on vapor concentration, delta range, and averaging-time. METHODS A Triple Water Vapor Isotope Analyzer (T-WVIA) was used to evaluate the accuracy and Precision of δ(2) H, δ(18) O and δ(17) O measurements. The sensitivity of accuracy and Precision to water vapor concentration was evaluated using two international standards (GISP and SLAP2). The sensitivity of Precision to delta value was evaluated using four working standards spanning a large delta range. The sensitivity of Precision to averaging-time was assessed by measuring one standard continuously for 24 hours. RESULTS Overall, the accuracy and Precision of the δ(2) H, δ(18) O and δ(17) O measurements were high. Across all vapor concentrations, the accuracy of δ(2) H, δ(18) O and δ(17) O observations ranged from 0.10‰ to 1.84‰, 0.08‰ to 0.86‰ and 0.06‰ to 0.62‰, respectively, and the Precision ranged from 0.099‰ to 0.430‰, 0.009‰ to 0.080‰ and 0.022‰ to 0.054‰, respectively. The accuracy and Precision of all isotope measurements were sensitive to concentration, with the higher accuracy and Precision generally observed under moderate vapor concentrations (i.e., 10000-15000 ppm) for all isotopes. The Precision was also sensitive to the range of delta values, although the effect was not as large compared with the sensitivity to concentration. The Precision was much less sensitive to averaging-time than the concentration and delta range effects. CONCLUSIONS The accuracy and Precision Performance of the T-WVIA depend on concentration but depend less on the delta value and averaging-time. The instrument can simultaneously and continuously measure δ(2) H, δ(18) O and δ(17) O values in water vapor, opening a new window to better understand ecological, hydrological and meteorological processes. Copyright © 2016 John Wiley & Sons, Ltd.
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water vapor δ2h δ18o and δ17o measurements using an off axis integrated cavity output spectrometer sensitivity to water vapor concentration delta value and averaging time
Author, 2016Co-Authors: Chao Tian, Lixin Wang, Kimberly A NovickAbstract:RATIONALE High-Precision analysis of atmospheric water vapor isotope compositions, especially δ(17) O values, can be used to improve our understanding of multiple hydrological and meteorological processes (e.g., differentiate equilibrium or kinetic fractionation). This study focused on assessing, for the first time, how the accuracy and Precision of vapor δ(17) O laser spectroscopy measurements depend on vapor concentration, delta range, and averaging-time. METHODS A Triple Water Vapor Isotope Analyzer (T-WVIA) was used to evaluate the accuracy and Precision of δ(2) H, δ(18) O and δ(17) O measurements. The sensitivity of accuracy and Precision to water vapor concentration was evaluated using two international standards (GISP and SLAP2). The sensitivity of Precision to delta value was evaluated using four working standards spanning a large delta range. The sensitivity of Precision to averaging-time was assessed by measuring one standard continuously for 24 hours. RESULTS Overall, the accuracy and Precision of the δ(2) H, δ(18) O and δ(17) O measurements were high. Across all vapor concentrations, the accuracy of δ(2) H, δ(18) O and δ(17) O observations ranged from 0.10‰ to 1.84‰, 0.08‰ to 0.86‰ and 0.06‰ to 0.62‰, respectively, and the Precision ranged from 0.099‰ to 0.430‰, 0.009‰ to 0.080‰ and 0.022‰ to 0.054‰, respectively. The accuracy and Precision of all isotope measurements were sensitive to concentration, with the higher accuracy and Precision generally observed under moderate vapor concentrations (i.e., 10000-15000 ppm) for all isotopes. The Precision was also sensitive to the range of delta values, although the effect was not as large compared with the sensitivity to concentration. The Precision was much less sensitive to averaging-time than the concentration and delta range effects. CONCLUSIONS The accuracy and Precision Performance of the T-WVIA depend on concentration but depend less on the delta value and averaging-time. The instrument can simultaneously and continuously measure δ(2) H, δ(18) O and δ(17) O values in water vapor, opening a new window to better understand ecological, hydrological and meteorological processes. Copyright © 2016 John Wiley & Sons, Ltd.
Saket Pande - One of the best experts on this subject based on the ideXlab platform.
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laboratory calibration and Performance evaluation of low cost capacitive and very low cost resistive soil moisture sensors
Sensors, 2020Co-Authors: Soham Adla, Neeraj Rai, Sri Karumanchi, Shivam Tripathi, Markus Disse, Saket PandeAbstract:Soil volumetric water content ( V W C ) is a vital parameter to understand several ecohydrological and environmental processes. Its cost-effective measurement can potentially drive various technological tools to promote data-driven sustainable agriculture through supplemental irrigation solutions, the lack of which has contributed to severe agricultural distress, particularly for smallholder farmers. The cost of commercially available V W C sensors varies over four orders of magnitude. A laboratory study characterizing and testing sensors from this wide range of cost categories, which is a prerequisite to explore their applicability for irrigation management, has not been conducted. Within this context, two low-cost capacitive sensors-SMEC300 and SM100-manufactured by Spectrum Technologies Inc. (Aurora, IL, USA), and two very low-cost resistive sensors-the Soil Hygrometer Detection Module Soil Moisture Sensor (YL100) by Electronicfans and the Generic Soil Moisture Sensor Module (YL69) by KitsGuru-were tested for Performance in laboratory conditions. Each sensor was calibrated in different repacked soils, and tested to evaluate accuracy, Precision and sensitivity to variations in temperature and salinity. The capacitive sensors were additionally tested for their Performance in liquids of known dielectric constants, and a comparative analysis of the calibration equations developed in-house and provided by the manufacturer was carried out. The value for money of the sensors is reflected in their Precision Performance, i.e., the Precision Performance largely follows sensor costs. The other aspects of sensor Performance do not necessarily follow sensor costs. The low-cost capacitive sensors were more accurate than manufacturer specifications, and could match the Performance of the secondary standard sensor, after soil specific calibration. SMEC300 is accurate ( M A E , R M S E , and R A E of 2.12%, 2.88% and 0.28 respectively), precise, and performed well considering its price as well as multi-purpose sensing capabilities. The less-expensive SM100 sensor had a better accuracy ( M A E , R M S E , and R A E of 1.67%, 2.36% and 0.21 respectively) but poorer Precision than the SMEC300. However, it was established as a robust, field ready, low-cost sensor due to its more consistent Performance in soils (particularly the field soil) and superior Performance in fluids. Both the capacitive sensors responded reasonably to variations in temperature and salinity conditions. Though the resistive sensors were less accurate and precise compared to the capacitive sensors, they performed well considering their cost category. The YL100 was more accurate ( M A E , R M S E , and R A E of 3.51%, 5.21% and 0.37 respectively) than YL69 ( M A E , R M S E , and R A E of 4.13%, 5.54%, and 0.41, respectively). However, YL69 outperformed YL100 in terms of Precision, and response to temperature and salinity variations, to emerge as a more robust resistive sensor. These very low-cost sensors may be used in combination with more accurate sensors to better characterize the spatiotemporal variability of field scale soil moisture. The laboratory characterization conducted in this study is a prerequisite to estimate the effect of low- and very low-cost sensor measurements on the efficiency of soil moisture based irrigation scheduling systems.
Chao Tian - One of the best experts on this subject based on the ideXlab platform.
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water vapor δ 2 h δ 18 o and δ 17 o measurements using an off axis integrated cavity output spectrometer sensitivity to water vapor concentration delta value and averaging time
Rapid Communications in Mass Spectrometry, 2016Co-Authors: Chao Tian, Lixin Wang, Kimberly A NovickAbstract:RATIONALE High-Precision analysis of atmospheric water vapor isotope compositions, especially δ(17) O values, can be used to improve our understanding of multiple hydrological and meteorological processes (e.g., differentiate equilibrium or kinetic fractionation). This study focused on assessing, for the first time, how the accuracy and Precision of vapor δ(17) O laser spectroscopy measurements depend on vapor concentration, delta range, and averaging-time. METHODS A Triple Water Vapor Isotope Analyzer (T-WVIA) was used to evaluate the accuracy and Precision of δ(2) H, δ(18) O and δ(17) O measurements. The sensitivity of accuracy and Precision to water vapor concentration was evaluated using two international standards (GISP and SLAP2). The sensitivity of Precision to delta value was evaluated using four working standards spanning a large delta range. The sensitivity of Precision to averaging-time was assessed by measuring one standard continuously for 24 hours. RESULTS Overall, the accuracy and Precision of the δ(2) H, δ(18) O and δ(17) O measurements were high. Across all vapor concentrations, the accuracy of δ(2) H, δ(18) O and δ(17) O observations ranged from 0.10‰ to 1.84‰, 0.08‰ to 0.86‰ and 0.06‰ to 0.62‰, respectively, and the Precision ranged from 0.099‰ to 0.430‰, 0.009‰ to 0.080‰ and 0.022‰ to 0.054‰, respectively. The accuracy and Precision of all isotope measurements were sensitive to concentration, with the higher accuracy and Precision generally observed under moderate vapor concentrations (i.e., 10000-15000 ppm) for all isotopes. The Precision was also sensitive to the range of delta values, although the effect was not as large compared with the sensitivity to concentration. The Precision was much less sensitive to averaging-time than the concentration and delta range effects. CONCLUSIONS The accuracy and Precision Performance of the T-WVIA depend on concentration but depend less on the delta value and averaging-time. The instrument can simultaneously and continuously measure δ(2) H, δ(18) O and δ(17) O values in water vapor, opening a new window to better understand ecological, hydrological and meteorological processes. Copyright © 2016 John Wiley & Sons, Ltd.
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water vapor δ2h δ18o and δ17o measurements using an off axis integrated cavity output spectrometer sensitivity to water vapor concentration delta value and averaging time
Author, 2016Co-Authors: Chao Tian, Lixin Wang, Kimberly A NovickAbstract:RATIONALE High-Precision analysis of atmospheric water vapor isotope compositions, especially δ(17) O values, can be used to improve our understanding of multiple hydrological and meteorological processes (e.g., differentiate equilibrium or kinetic fractionation). This study focused on assessing, for the first time, how the accuracy and Precision of vapor δ(17) O laser spectroscopy measurements depend on vapor concentration, delta range, and averaging-time. METHODS A Triple Water Vapor Isotope Analyzer (T-WVIA) was used to evaluate the accuracy and Precision of δ(2) H, δ(18) O and δ(17) O measurements. The sensitivity of accuracy and Precision to water vapor concentration was evaluated using two international standards (GISP and SLAP2). The sensitivity of Precision to delta value was evaluated using four working standards spanning a large delta range. The sensitivity of Precision to averaging-time was assessed by measuring one standard continuously for 24 hours. RESULTS Overall, the accuracy and Precision of the δ(2) H, δ(18) O and δ(17) O measurements were high. Across all vapor concentrations, the accuracy of δ(2) H, δ(18) O and δ(17) O observations ranged from 0.10‰ to 1.84‰, 0.08‰ to 0.86‰ and 0.06‰ to 0.62‰, respectively, and the Precision ranged from 0.099‰ to 0.430‰, 0.009‰ to 0.080‰ and 0.022‰ to 0.054‰, respectively. The accuracy and Precision of all isotope measurements were sensitive to concentration, with the higher accuracy and Precision generally observed under moderate vapor concentrations (i.e., 10000-15000 ppm) for all isotopes. The Precision was also sensitive to the range of delta values, although the effect was not as large compared with the sensitivity to concentration. The Precision was much less sensitive to averaging-time than the concentration and delta range effects. CONCLUSIONS The accuracy and Precision Performance of the T-WVIA depend on concentration but depend less on the delta value and averaging-time. The instrument can simultaneously and continuously measure δ(2) H, δ(18) O and δ(17) O values in water vapor, opening a new window to better understand ecological, hydrological and meteorological processes. Copyright © 2016 John Wiley & Sons, Ltd.
Lisette P Waits - One of the best experts on this subject based on the ideXlab platform.
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a new method for estimating the size of small populations from genetic mark recapture data
Molecular Ecology, 2005Co-Authors: Craig R Miller, Paul Joyce, Lisette P WaitsAbstract:The use of non-invasive genetic sampling to estimate population size in elusive or rare species is increasing. The data generated from this sampling differ from traditional mark-recapture data in that individuals may be captured multiple times within a session or there may only be a single sampling event. To accommodate this type of data, we develop a method, named capwire, based on a simple urn model containing individuals of two capture probabilities. The method is evaluated using simulations of an urn and of a more biologically realistic system where individuals occupy space, and display heterogeneous movement and DNA deposition patterns. We also analyse a small number of real data sets. The results indicate that when the data contain capture heterogeneity the method provides estimates with small bias and good coverage, along with high accuracy and Precision. Performance is not as consistent when capture rates are homogeneous and when dealing with populations substantially larger than 100. For the few real data sets where N is approximately known, capwire's estimates are very good. We compare capwire's Performance to commonly used rarefaction methods and to two heterogeneity estimators in program capture: Mh-Chao and Mh-jackknife. No method works best in all situations. While less precise, the Chao estimator is very robust. We also examine how large samples should be to achieve a given level of accuracy using capwire. We conclude that capwire provides an improved way to estimate N for some DNA-based data sets.
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a new method for estimating the size of small populations from genetic mark recapture data
Molecular Ecology, 2005Co-Authors: Craig R Miller, Paul Joyce, Lisette P WaitsAbstract:The use of non-invasive genetic sampling to estimate population size in elusive or rare species is increasing. The data generated from this sampling differ from traditional mark–recapture data in that individuals may be captured multiple times within a session or there may only be a single sampling event. To accommodate this type of data, we develop a method, named capwire, based on a simple urn model containing individuals of two capture probabilities. The method is evaluated using simulations of an urn and of a more biologically realistic system where individuals occupy space, and display heterogeneous movement and DNA deposition patterns. We also analyse a small number of real data sets. The results indicate that when the data contain capture heterogeneity the method provides estimates with small bias and good coverage, along with high accuracy and Precision. Performance is not as consistent when capture rates are homogeneous and when dealing with populations substantially larger than 100. For the few real data sets where N is approximately known, capwire's estimates are very good. We compare capwire's Performance to commonly used rarefaction methods and to two heterogeneity estimators in program capture: Mh-Chao and Mh-jackknife. No method works best in all situations. While less precise, the Chao estimator is very robust. We also examine how large samples should be to achieve a given level of accuracy using capwire. We conclude that capwire provides an improved way to estimate N for some DNA-based data sets. Capwire is available at http://www.cnr.uidaho.edu/lecg/.