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Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller is tested under static and dynamic load conditions. The simulation and models are done by using MATLAB/Simulink. The simulation results from the proposed NARMA-L2 controller have been compared with existing Perturb and observe PO-MPPT and Incremental Conductance INC -MPPT methods.

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Publication Date
Wed Mar 27 2024
Journal Name
International Journal Of Mechatronics And Applied Mechanics
A ROBUST CONTROLLER DESIGN FOR AN INLET THROTTLING SPEED CONTROL SYSTEM FOR A ROTARY ACTUATOR
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In this paper, a novel flow control strategy which is the inlet throttled pump was used to design an angular velocity control system for rotary actuator. Inlet throttled systems have good performance in addition to their high efficiency compared to traditional valve-controlled systems. The flow in the proposed system is adjusted by a valve that is positioned at the pump inlet with the purpose of reducing the energy loses across the valve. This regulated flow is used then to control the actuator angular velocity. The system was modeled and the open loop stability and performance were studied. In order to improve the system performance, proportional-integral-derivative (PID) and H-infinity controllers have been designed. The multiplicative un

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Non-newtonian Fluid Mechanics
On the stability of the BEK family of rotating boundary-layer flows for power-law fluids
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Publication Date
Sun Jan 01 2012
Journal Name
Aip Conference Proceedings
The electrical conductivity and thermoelectric power dependence on the thicknesses for thermally deposited thin CdS films
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Publication Date
Thu Jan 29 2026
Journal Name
Journal Of Optics
A review on beam-shaping techniques for high-power and compact fiber-coupled diode laser system
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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Generative Adversarial Network for Imitation Learning from Single Demonstration
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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

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Publication Date
Fri Jan 01 2016
Journal Name
Machine Learning And Data Mining In Pattern Recognition
A New Strategy for Case-Based Reasoning Retrieval Using Classification Based on Association
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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Economics And Finance Studies
INTEGRATION BETWEEN COBIT AND COSO FOR INTERNAL CONTROL AND ITS REFLECTION ON AUDITING RISK WITH CORPORATE GOVERNANCE AS THE MEDIATING VARIABLE
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Publication Date
Sat Dec 01 2018
Journal Name
The Egyptian Journal Of Remote Sensing And Space Science
Evaluate 3D laser point clouds registration for cultural heritage documentation
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Publication Date
Mon Jul 01 2019
Journal Name
Journal Of Physics: Conference Series
Fusion Power Density and Radiation Losses Characteristics for Tritium Fusion Reactions
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A new data for Fusion power density has been obtained for T-3He and T-T fusion reactions, power density is a substantial term in the researches related to the fusion energy generation and ignition calculations of magnetic confined systems. In the current work, thermal nuclear reactivities, power densities of a fusion reactors and the ignition condition inquiry are achieved by using a new and accurate formula of cross section, the maximum values of fusion power density for T-3He and TT reaction are 1.1×107 W/m3 at T=700 KeV and 4.7×106 W/m3 at T=500 KeV respectively, While Zeff suggested to be 1.44 for the two reactions. Bremsstrahlung radiation has also been determined to reaching self- sustaining reactors, Bremsstrahlung values are 4.5×

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Publication Date
Wed Sep 11 2019
Journal Name
Journal Of Mechanical Engineering Research And Developments
INDUSTRIAL TRACKING CAMERA AND PRODUCT VISION DETECTION SYSTEM
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