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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics
Kasim Mousa Al-Aubidy
Philadelphia University
Computer Science & IT Electrical & Electronics Engineering

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Embedded control unit design for energy management in smart homes Rawan Mazen Abusharia; Kasim Mousa Al-Aubidy
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.4103

Abstract

This paper deals with smart home energy management through load scheduling and optimal use of available energy sources. In this study, three energy sources were considered: the national electricity grid, photovoltaic (PV) energy, and the storage unit. The PV array can provide the maximum power to the load at a given operating point where the output power changes with temperature, radiation and load. Therefore, a real-time controller is proposed to track the maximum power. An energy management algorithm has been proposed in a smart home to achieve the main goal of making the electricity bill as low as possible. The algorithm involves scheduling loads by assigning a priority to each load. The loads are supplied with the required power according to their priorities and the available energy. The obtained results indicate that supplying the PV system with a fuzzy-based MPPT indicates an increase in system efficiency. The results also showed that the use of energy management based on load scheduling led to a significant reduction in the electricity bill.
IoT-based smart monitoring and management system for fish farming Abdallah Waddah Al-Mutairi; Kasim Mousa Al-Aubidy
Bulletin of Electrical Engineering and Informatics Vol 12, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i3.3365

Abstract

Fish farming is still controlled and managed in the traditional way where water quality and fish feeding are manually controlled. There is a need to use computer and communication technology in fish farms for remote monitoring and control. This paper deals with the design and implementation of an internet of things (IoT) based system for real-time monitoring, control and management of fish farming. The design of such a system is based on measuring different types of variables and using the information to control fish growth and increase productivity. Each fish pond is a node in a wireless sensor network. The node contains an embedded microcontroller connected to a set of sensors and actuators and a wireless communication module. Two fuzzy controllers are designed to control the water quality in the ponds as well as the environment using five sensors in each pond plus three environmental sensors. Practical results indicate the accuracy of the measurement system compared to the results obtained from commercial devices used on the farm. These results also showed that the proposed approach achieves the best performance of the real-time monitoring and control system in fish ponds.
Neuro-fuzzy-based anti-swing control of automatic tower crane Saleh B. Al-Tuhaifi; Kasim Mousa Al-Aubidy
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 4: August 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i4.24044

Abstract

Controlling the position of the final load and the anti-swing control of the loads during the operation of the tower crane are challenging tasks. These are the most important control issues for safe operation, which are difficult to achieve easily with conventional control systems. Hence, the need to integrate the concepts of soft-computing into the tower crane control system. The aim of this research work is to design an adaptive-network-based fuzzy inference system (ANFIS) controller to move the payload to the final position with the lowest possible swing angle. To evaluate the ability of the proposed controller to meet the control requirements, its performance was compared to three other controllers: a conventional proportional derivative (PD) controller, a fuzzy-tuned PD controller and a fuzzy controller. MATLAB-based computer simulations of the crane and controllers were carried out to verify and compare the performance of the proposed controllers. The obtained results show the effectiveness of the ANFIS-based controller in adjusting the load position while keeping the load fluctuations small at the final position. The load oscillation angle is about ±2.28° with the ANFIS controller while it is about ±10° when using the PD controller. In addition, only one ANFIS controller is used for both load position and swing angle control.
Co-Authors Abdallah Waddah Al-Mutairi Rawan Mazen Abusharia Saleh B. Al-Tuhaifi