This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fuel cell system and to achieve the stability of the desired output voltage of fuel cell. The numerical simulation results (MATLAB) package along with the schematic design experimental work using Spartan-3E xc3s500e-4fg320 board with the Xilinx development tool Integrated Software Environment (ISE) version 14.7 and using Verilog hardware description language for design testing are illustrated the performance enhancement of the proposed an adaptive intelligent FPGA-PID-NN controller in terms of error voltage reduction and generating optimal value of the hydrogen partial pressure action (PH2) without oscillation in the output and no saturation state when these results are compared with other controllers.
The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots. To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura
... Show MoreProductivity estimating of ready mixed concrete batch plant is an essential tool for the successful completion of the construction process. It is defined as the output of the system per unit of time. Usually, the actual productivity values of construction equipment in the site are not consistent with the nominal ones. Therefore, it is necessary to make a comprehensive evaluation of the nominal productivity of equipment concerning the effected factors and then re-evaluate them according to the actual values.
In this paper, the forecasting system was employed is an Artificial Intelligence technique (AI). It is represented by Artificial Neural Network (ANN) to establish the predicted model to estimate wet ready mixe
... Show MoreAbstract
This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine
... Show MoreThe present study discusses the significant role of the historical memory in all the Spanish society aspects of life. When a novelist takes the role and puts on the mask of one of the novel’s protagonists or hidden characters, his memory of the events becomes the keywords of accessing the close-knit fabric of society and sheds lights on deteriorating social conceptions in a backwards social reality that rejects all new progressive ideas and modernity. Through concentrating on the society flawing aspects and employing everything of his stored memory, the author uses sarcasm to criticize and change such old deteriorating reality conceptions.
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... Show MoreA seismicity study of khanaqin city and surrounding area is carried out. More than 270
quakes between 22 Nov. to 30 Dec. 2013 are recorded by Iraqi Seismic Network (ISN).
Analyses of these events show earthquakes magnitude range between (1.2 – 5.6) degree,
focal depth between (4 – 27) km. Seismotectonic map for studied area is drawn .
Isointensity maps for the felt earthquakes are drawn and show the intensity range
between (I-VII) according to the modified Mercalli scale. Fault plane solutions for four
events in the study area indicate a reverse strike slip solution along planes with NW –SE
direction
Information security contributes directly to increase the level of trust between the government’s departments by providing an assurance of confidentiality, integrity, and availability of sensitive governmental information. Many threats that are caused mainly by malicious acts can shutdown the egovernment services. Therefore the governments are urged to implement security in e-government projects.
Some modifications were proposed to the security assessment multi-layer model (Sabri model) to be more comprehensive model and more convenient for the Iraqi government. The proposed model can be used as a tool to assess the level of security readiness of government departments, a checklist for the required security measures and as a commo
Risperidone is an atypical antipsychotic drug that is used for treating schizophrenia, bipolar mania, and autism. Risperidone rebalances dopamine and serotonin to improve thinking, mood, and behavior by working on dopamine and serotonin α2receptor antagonism. Risperidone has poor solubility and high permeability through the intestine, so it belongs to Biopharmaceutical Classification System (BCS) class II exhibits poor oral biopharmaceutical properties.
The aim of the present work was to improve solubility and dissolution of Risperidone by preparing nanosuspension using different stabilizers and different solvents in a method known as solvent-antisolvent precipitation method. Twenty-eight formulas were prepared
... Show MoreA genetic algorithm model coupled with artificial neural network model was developed to find the optimal values of upstream, downstream cutoff lengths, length of floor and length of downstream protection required for a hydraulic structure. These were obtained for a given maximum difference head, depth of impervious layer and degree of anisotropy. The objective function to be minimized was the cost function with relative cost coefficients for the different dimensions obtained. Constraints used were those that satisfy a factor of safety of 2 against uplift pressure failure and 3 against piping failure.
Different cases reaching 1200 were modeled and analyzed using geo-studio modeling, with different values of input variables. The soil wa
Linear attenuation coefficient of polymer composite for beta particles and bremsstrahlung ray were investigated as a function of the absorber thickness and energy. The attenuation coefficient were obtained using NaI(Tl) energy selective scintillation counter with 90Sr/90Y beta source having an energy range from 0.1-1.1 MeV. The present results show the capability of this composite to absorber beta particles and bremsstrahlung ray that yield from it. That’s mean it is useful to choice this composite for radiation shielding of beta ray with low thickness.
Machine learning-based techniques are used widely for the classification of images into various categories. The advancement of Convolutional Neural Network (CNN) affects the field of computer vision on a large scale. It has been applied to classify and localize objects in images. Among the fields of applications of CNN, it has been applied to understand huge unstructured astronomical data being collected every second. Galaxies have diverse and complex shapes and their morphology carries fundamental information about the whole universe. Studying these galaxies has been a tremendous task for the researchers around the world. Researchers have already applied some basic CNN models to predict the morphological classes
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