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.
In this work, thermodynamic efficiency of individual cell and stack of cells (two cells) has been computed by studying the variation of voltage produced during an operation time of 30 min as a result of the affected parameters:- stoichiometric feed ratio, flow field design on single cell and feed distribution on stack of cells. The experiments were carried out by using two cells, one with serpentine flow field and the other with spiral flow field. These cells were fed with hydrogen and oxygen at low volumetric flow rates from 1 to 2 ml/sec and stoichiometric ratios of fuel (H2) to oxidant (O2) as 1:2, 1:1 and 2:1 respectively. The results showed that
... Show MoreThe convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog
... Show MorePhotoacoustic is a unique imaging method that combines the absorption contrast of light or radio frequency waves with ultrasound resolution. When the deposition of this energy is sufficiently short, a thermo-elastic expansion takes place whereby acoustic waves are generated. These waves can be recorded and stored to construct an image. This work presents experimental procedure of laser photoacoustic two dimensional imaging to detect tumor embedded within normal tissue. The experimental work is accomplished using phantoms that are sandwiched from fish heart or blood sac (simulating a tumor) 1-14mm mean diameter embedded within chicken breast to simulate a real tissue. Nd: YAG laser of 1.064μm and 532nm wavelengths, 10ns pulse duration, 4
... Show MoreThis report explores emerging techniques to boost multimedia transfer effectiveness, given the escalating need for improved quality and performance in multimedia interactions. The analysis involves a thorough literature assessment and comparison of present strategies to pinpoint key tendencies and propose novel approaches. The methodology involves examining recent technological enhance ments in video coding standards, quality appraisal methods, and compression tech niques. Specific domains investigated comprise firmware component architectures, 4D indexing structures, and iterative filtering frameworks. The study in addition weighs tradeoffs between video quality, encoding intricacy, and bitrate demands. Key determinations consist of
... Show MoreThe study dealt with measuring the impact of the availability of each of the content elements of the interaction, electronic services, and information on the evaluation of the users of the government website for its effectiveness in terms of the site’s functions and for measuring the site’s ability to present the organization’s tasks to customer groups.
Authority is concerned with measuring the confidence of customers in the content of the site, and in the organization as a whole. Validity is related to measuring the effectiveness of employing the site’s content to achieve the goal of its creation and in communicating with customers. Availability It is for measuring the ease of use of the site. The relevance, which means
... Show MoreThe paper generates a geological model of a giant Middle East oil reservoir, the model constructed based on the field data of 161 wells. The main aim of the paper was to recognize the value of the reservoir to investigate the feasibility of working on the reservoir modeling prior to the final decision of the investment for further development of this oilfield. Well log, deviation survey, 2D/3D interpreted seismic structural maps, facies, and core test were utilized to construct the developed geological model based on comprehensive interpretation and correlation processes using the PETREL platform. The geological model mainly aims to estimate stock-tank oil initially in place of the reservoir. In addition, three scenarios were applie
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