Ensemble evaluation of hydrological model hypotheses

It is demonstrated for the first time how model parameter, structural and data uncertainties can be accounted for explicitly and simultaneously within the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. As an example application, 72 variants of a single soil moisture accounting store are tested as simplified hypotheses of runoff generation at six experimental grassland field-scale lysimeters through model rejection and a novel diagnostic scheme. The fields, designed as replicates, exhibit different hydrological behaviors which yield different model performances. For fields with low initial discharge levels at the beginning of events, the conceptual stores considered reach their limit of applicability. Conversely, one of the fields yielding more discharge than the others, but having larger data gaps, allows for greater flexibility in the choice of model structures. As a model learning exercise, the study points to a “leaking” of the fields not evident from previous field experiments. It is discussed how understanding observational uncertainties and incorporating these into model diagnostics can help appreciate the scale of model structural error

A New Self-Tuning Nonlinear PID Motion Control for One-Axis Servomechanism with Uncertainty Consideration

This paper introduces a new study for one-axis servomechanism with consideration the parameter variation and system uncertainty. Also, a new approach for high-performance self-tuning nonlinear PID control was developed to track a preselected profile with high accuracy. Moreover, a comparison study between the proposed control technique and the well-known controllers (PID and Nonlinear PID). The optimal control parameters were determined based on the COVID-19 optimization technique. The parameters of the servomechanism system changed randomly at a preselected range through the online simulation. The change of these parameters acts as the nonlinearity resources (friction, backlash, environmental effects) and system uncertainty. A comparative study between the linear and nonlinear models had been accomplished and investigated. The results show that the proposed controller can track several operating points with high accuracy, low rise time, and small overshoot

Parallel distribution compensation PID based on Takagi-Sugeno fuzzy model applied on egyptian load frequency control

This paper presents a new technique for a Takagi-Sugeno (TS) fuzzy parallels distribution compensation-PID'S (TSF-PDC-PID'S) to improve the performance of Egyptian load frequency control (ELFC). In this technique, the inputs to a TS Fuzzy model are the parameters of the change of operating points. The TS Fuzzy model can definite the suitable PID control for a certain operating point. The parameters of PID'S controllers are obtained by ant colony optimization (ACO) technique in each operating point based on an effective cost function. The system controlled by the proposed TSF-PDC-PID’S is investigated under different types of disturbances, uncertainty and parameters variations. The simulation results ensure that the TSF-PDC-PID'S can update the suitable PID controller at several operating points so, it has a good dynamic response under many types of disturbances compared to fixed Optimal PID controller

Fuzzy type two self-tuning technique of single neuron PID controller for brushless DC motor based on a COVID-19 optimization

This paper presents an efficient interval type 2 fuzzy (IT2F) based on a single neuron proportional–integral–derivative (PID), also known as IT2FSNPID controller. The main purpose of the proposed control technique is to track the motion profile of the brushless DC (BLDC) motor. Also, a comparative study was investigated fuzzy type 1 (FT1) and IT2F. IT2F can treat the uncertainty and nonlinearity of the BLDC motor drive electric system in contrast to FT1. The parameters of each control technique were obtained using a new COVID-19 optimization algorithm according to an objective function. Moreover, several tests had been performed to ensure the ability of fuzzy type to absorb the system uncertainty and nonlinearity. All controllers were utilized to operate the BLDC motor sudden change in load and continuous load. The simulation results show that the IT2FSNPID can improve the dynamic response of linear and nonlinear of the same BLDC motor and accommodate the system uncertainty significantly

Model reference self-tuning fractional order PID control based on for a power system stabilizer

This paper presents a novel approach of self-tuning for a Modified Fractional Order PID (MFOPID) depends on the Model Reference Adaptive System (MRAS). The proposed self-tuning controller is applied to Power System Stabilizer (PSS). Takaji-Sugeno (TS) fuzzy logic technique is used to construct the MFOPID controller. The objective of MRAS is to update the five parameters of Takaji-Sugeno Modified FOPID (TSMFOPID) controller online. For different operating points of PSS, MRAS is applied to investigate the effectiveness of proposed controllers. The harmony optimization technique used to obtain the optimal parameters of TSMFOPID controllers and MRAS parameters. For different operating points with different disturbance under parameters variations the simulation results are obtained. This is to show that Self-Tuning of TSMFOPID based on (MRAS) have better performance than the fixed parameters TSMOFOPID controller

Effect of Nitrophoska® and irrigation interval on root and sugar yield of sugar beet (Beta vulgaris L.), Gezira State, Sudan

Sugar beet is one of the promising crops in the Sudan due to its high root, sugar yield and by-products as an industrial crop. The crop is also a promising alternative energy crop for the production of ethanol. An experiment was conducted at the experimental Farm of the Faculty of Agricultural Sciences, University of Gezira, Wad Medani, Sudan, during seasons 2012/13 and 2013/14. The objective was to investigate the effects of irrigation intervals (7, 14 and 21 days) and Nitrophoska (NPK compound fertilizer) rates (0, 100, 150 and 200 kg/ha) on root and sugar yield of sugar beet (Ballade cultivar) under Gezira conditions. Split-plot design with three replicates was used. Irrigation intervals were allotted to the main plots and Nitrophoska rates to the subplots. Results showed that shortening irrigation intervals from 21 to 14 and 7 days increased root diameter, root weight and root and sugar yields in both seasons. In addition, Nitrophoska rate of 150 kg/ha substantially improved most of the studied root characters and sugar yield in both seasons. Depending on the results of this study, to obtain high root and sugar yields from sugar beet Ballade cultivar, it could be recommended  to apply 150 kg/ha of  Nitrophoska  and  irrigate every 7 to14 days.   بنجر السكر من المحاصيل الواعدة في السودان وذلك نسبة لإنتاجيته العالية من الجذور والسكر ومنتجاته كمحصول صناعي. بنجر السكر من محاصيل الطاقة البديلة الواعدة لإنتاج الإيثانول. أجريت التجربة في المزرعة التجريبية، كلية العلوم الزراعية، جامعة الجزيرة، وادمدني، السودان في الموسمين 2012/ 13 و 2013/14م على التوالي. الهدف من التجربة هو دراسة تأثير فترات الري (7 و14 و21 يوم) ومعدلات سماد النيتروفوسكا المركب (0 و100 و150 و200 كجم للهكتار) على إنتاجية الجذور والسكر لبنجر السكر (صنف بلدي) تحت ظروف الجزيرة. تم إستخدام تصميم القطع المنشقة بثلاث تكرارات. أوضحت النتائج أن تقليل فترات الري من 21 الي 14 و7 زاد قطر الجذر ووزن الجذر وإنتاجية الجذور والسكر في كلا الموسمين. زيادة معدلات سماد النيتروفوسكا المركب من 0 الى أكثر 150 كجم للهكتار حسن بشكل كبير أغلب الصفات المدروسة للجذر وإنتاجية السكر في كلا الموسمين. إعتماداً على نتائج هذه الدراسة للحصول على أعلى إنتاجية من الجذور والسكر لمحصول بنجر السكر نوصي بإضافة سماد النيتروفوسكا بمعدل 150 كجم/هكتار على أن يروى المحصول كل 7 إلى 14 يو

Molecular Characterization of Egyptian Isolates of Lactobacillus and Bifidobacterium

Abstract: Strains of Lactobacillus and Bifidobacterium were isolated from processed milk collected in Cairo, Egypt. Lactobacilli was isolated on Acetate media (SL) of Rogosa and Mitchell-Weisman. While Bifidobacterium was isolated on DSM medium (Difco Sporulation Medium). The isolates were characterized microscopically, morphologically and by some biochemical tests. DNA was extracted from the specified isolates using (Qiagen, Germany. Cat #51306) and species-specific primers for Lactobacillus and Bifidobacterium were designed to amplify the 16s rDNA gene as a conserved region in the bacterial DNA. Elution of the target band from the gel was performed efficiently and the 16S rDNA region was subjected to sequencing using Sequencer ABI PRISM 3730XL Analyzer. The sequencing data obtained suggested that the two studied isolates were (at the genus level) designated as Lactobacillus and uncultured Bifidobacterium. When the sequencing data was aligned on http://www.ncbi.nlh.nih.gov, it shows 88% homology and expected value of 7e-164 to Lactobacillus kiranofaceins but dendogram tree shows more homology to Lactobacillus plantarum family. While the other sample showed 91% homology and expected value of 3e-113 with Uncultured Bifidobacterium Clone R333 16S rRNA gene. [Hashem S.; H

Design variable structure fuzzy control based on deep neural network model for servomechanism drive system

This paper presents a new scheme for variable structure (VS) fuzzy PD controller. The rule base of the fuzzy PD controller is tuned online. The purpose of the proposed controller is to track accurately a preselected position command for the servomechanism system. Therefore, this study establishes a model using a black-box modeling approach; simulations were performed based on real-time data collected by LabVIEW and processed using MATLAB. The input signal for the servomechanism driver is a pseudo-random binary sequence that considers violent excitation in the frequency interval. The candidate models were obtained using linear least squares, nonlinear least squares, and deep neural network (DNN). The validation results proved that the identified model based on DNN has the smallest mean square errors. Then, the DNN identified model was used to design the proposed control techniques. A comparison had been executed between the VS fuzzy PD control, the conventional PD control, and the fixed structure fuzzy PD control. The experimental results confirm the proposed VS fuzzy PD control can absorb the nonlinear behavior of the system. The speed regulation test, it reduces the rise time from 50% to 56%. While continuously changing in speed, it has the smallest tracking error (0.412 inches)