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INDONESIA
Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Published by IAES Indonesia Section and Partners
ISSN : 20893272     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the engineering of Telecommunication and Information Technology, Applied Computing & Computer, Instrumentation & Control, Electrical (Power), Electronics, and Informatics.
Arjuna Subject : -
Articles 22 Documents
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Search results for , issue "Vol 10, No 4: December 2022" : 22 Documents clear
ANFIS multi-tasking algorithm implementation scheme for ball-on-plate system stabilization Oussama Hadoune; Mohamed Benouaret
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 4: December 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i4.4216

Abstract

This paper presents the design and realization of a ball-on-plate system using a 3-degree-of-freedom parallel robot controlled by an adaptive neuro-fuzzy in-ference system. The ball-on-plate system is nonlinear, multivariable, with an under-actuated feature. Initially, the parallel robot is designed using SolidWorks and mechanized using a computer numerical control machine. Followed by the presentation of the ball-on-plate system mathematical model and the simplified model obtained. Afterwards, the inverse kinematics are performed to derive the appropriate angle for each servomotor. Eventually, the controller is designed and implemented in a double loop feedback scheme. A comparison between the proposed controller and a conventional proportional–integral–derivative controller in terms of time response, overshoot, and steady-state error is carried out. Furthermore, a comparison between sequential and asynchronous parallel processing is conducted for two different scenarios. The first scenario is when moving the ball to the origin while the second is for disturbance rejection. Simulation and experimental results show that the adaptive neuro-fuzzy inference system implemented using asynchronous parallel processing improves the real-time system stability by considerably decreasing oscillations as well as enhancing the ball movement smoothness with a small stead-state error.
A Comparison Between CCCV and VC Strategy for the Control of Battery Storage System in PV installation Achraf Nouri; Aymen Lachheb; Lilia El Amraoui
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 4: December 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i4.4040

Abstract

To meet demand with unpredictable daily and seasonal variations, the power grid faces significant hurdles in transmission and distribution. Electrical Energy Storage (EES), in which energy is stored in a specific state, depending on the technology utilized, and is converted to electrical energy, is acknowledged as a technology involved with significant potential for solving these difficulties. This paper deals with the modeling and control of a renewable energy production system based on solar panel. To improve the performance of the investigated power generation system, a lithium-ion battery storage system and bidirectional converter are associated to a solar panel that is unable to compensate for rapid variations in load power demand. In this situation, to meet load power demand, a rule-based energy management algorithm is used to share energy between the grid and the energy production system. Furthermore, two solutions are developed and compared: VC (Variable Current) and CC-CV (Constant Current Constant Voltage). The VC approach is used in conjunction with an energy management and protection system, whereas the CC-CV method is used in conjunction with an artificial neural network (ANN). The simulation results show that the VC control strategy give greater energy performance and installation stability compared to the CC-CV strategy, but not improved safety and protection of lithium-ion batteries.

Page 3 of 3 | Total Record : 22

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