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23
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Introduction
Control Engineering and AI enthusiast; dedicated professor committed to fostering intellectual growth, promoting collaboration, and pushing the boundaries of research. Exploring the powerful intersection of control systems and artificial intelligence for a technologically advanced future.
Current institution
Publications
Publications (23)
In this paper, we built a mathematical model for both longitudinal and lateral-directional dynamics of medium-sized commercial aircraft. The model was constructed by calculating the stability derivatives. It was then analyzed, and the results were investigated. Subsequently, a Stability Augmentation System was designed to stabilize the aircraft if...
This paper introduces the RGB Arabic Alphabet Sign Language (AASL) dataset. AASL comprises 7,856 raw and fully labelled RGB images of the Arabic sign language alphabets, which to our best knowledge is the first publicly available RGB dataset. The dataset is aimed to help those interested in developing real-life Arabic sign language classification m...
This paper improves on a recently proposed machine learning approach to assess and monitor the poverty status of Jordanian households. Without a doubt, accurate identification, tracking, and targeting households in poverty is a key to poverty alleviation. This work presents a nontraditional approach to the accurate prediction of poverty for Jordani...
The main challenge of automatic license plate recognition (ALPR) systems is that the overall performance is highly dependent upon the results of each component in the system’s pipeline. This paper proposes an improved ALPR system for the Jordanian license plates. Ceiling analysis is carried out to identify potential enhancements in each processing...
Pneumatic artificial muscles (PAMs) are excellent environmentally friendly actuators and springs that remain somewhat underutilized in the industry due to their hysteretic behavior, which makes predicting their behavior difficult. This paper presents a novel black-box approach that employs an adaptive-network-based fuzzy inference system (ANFIS) to...
The scope of this paper is focused on the multidimensional poverty problem in Jordan. Household expenditure and income surveys provide data that are used for identifying and measuring the poverty status of Jordanian households. However, carrying out such surveys is hard, time consuming, and expensive. Machine learning could revolutionize this proce...
Nowadays, quadcopters are present in many life applications which require the performance of automatic takeoff, traject- ory tracking, and automatic landing. Thus, researchers are aiming to enhance the performance of these vehicles through low-cost sensing solutions and the design of executable and robust control techniques. Due to high nonlinearit...
This paper improves a recently proposed twolayer hierarchical control strategy for the ACUREX plant at the Plataforma Solar de Almer´ıa. Improvements target the lower layer of the two-layer hierarchical control strategy. Two alternative systematic approaches are proposed and evaluated. The two approaches take explicit account of the measured distur...
This paper improves a recently proposed gain scheduling predictive control strategy for the ACUREX distributed solar collector field at the Plataforma Solar de Almería, in south-east Spain. Measured disturbances are an integral part of the plant and while simple classical, series and parallel, feedforward approaches have been proposed and used exte...
A nonlinear gain scheduling control strategy is proposed for a concentrated solar thermal power plant. The strategy involves the identification of local linear time-invariant state space models around a family of operating points, the design of corresponding local linear dual mode model-based predictive controllers and the selection of an appropria...
A nonlinear gain scheduling control strategy is proposed for a concentrated solar thermal power plant. The strategy involves the identification of local linear time-invariant state space models around a family of operating points, the design of corresponding local linear dual mode model-based predictive controllers and the selection of an appropria...
A model predictive control strategy for a concentrated solar thermal power plant is proposed. Design of the proposed controller is based on an estimated linear time-invariant state space model around a nominal operating point. The model is estimated directly from input-output data using the subspace identification method and taking into account the...
A model predictive control strategy for a concentrated solar thermal power plant is proposed. Design of the proposed controller is based on an estimated linear time-invariant state space model around a nominal operating point. The model is estimated directly from input-output data using the subspace identification method and taking into account the...
Recently, the utilization of low-head hydroelectric technologies has received a great attention for the expansion of distributed power systems into isolated regions that are difficult to be connected to the electrical grid, especially in developing countries. The use of gravitational vortex hydropower systems can be a renewable and suitable option...
