Publications Scientifiques

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Author: search.filters.author.Belaidi, Hadjira

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    Enhanced Signal Processing for Echo Detection Using Support Vector Machine, Weber’s Law Features, and Local Descriptors (LDP and LOOP)
    (Springer Science and Business Media, 2025) Hedir, Mehdia; Messaoui, Ali Zakaria; Messaoui, Aimen Abdelhak; Belaidi, Hadjira; Rouigueb, Abdenebi; Nemra, Abdelkrim
    Removing ground echoes from weather radar images is a critical task due to their substantial influence on the accuracy of processed meteorological data. These echoes often obscure the true atmospheric signals, particularly precipitation, which is essential for weather forecasting and analysis. In this study, we aim to develop advanced methods that not only eliminate ground echoes but also preserve precipitation signals, ensuring accurate meteorological observations. To achieve this, we explore the use of Local Descriptors based on Weber’s Law Descriptor (WLD) and combine it with the Local Binary Pattern (WLBP) descriptor, as well as introducing two novel descriptors: Local Directional Pattern (LDP) and Local Optimal-Oriented Pattern (LOOP). These descriptors are employed to capture various local features and patterns within the radar images that are crucial for distinguishing between ground echoes and precipitation. To automate the classification of these echo types, we leverage Support Vector Machine (SVM) classifiers, which have proven to be effective in high-dimensional pattern recognition tasks. Our proposed methods are rigorously tested at the Setif and Bordeaux sites, allowing for comprehensive evaluation under different weather conditions. The results from these tests demonstrate the effectiveness of the proposed techniques in accurately identifying and eliminating ground echoes while preserving precipitation. Specifically, the integration of LDP and LOOP significantly enhances the ability to differentiate between echoes, improving the robustness of the classifier in challenging environments. The outcomes indicate that these methods show considerable promise for practical applications in meteorological data processing, providing a reliable solution for improving the quality of weather radar data and supporting more accurate weather predictions.
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    Advanced Trajectory Planning Technique for Unmanned Underwater Vehicle Navigation with Enhanced Fuzzy Logic Control and Obstacle Avoidance Strategy
    (Springer Science and Business Media, 2025) Demim, Fethi; Saghor, Sofian; Belaidi, Hadjira; Rouigueb, Abdenebi; Messaoui, Ali Zakaria; Benatia, Mohamed Akram; Chergui, Mohamed; Nemra, Abdelkrim; Allam, Ahmed; Kobzili, Elhaouari
    Trajectory planning plays a pivotal role in Unmanned Underwater Vehicles (UUVs), and this study addresses this aspect by employing Rapidly-exploring Random Trees (RRT) and a Fuzzy Logic Control (FLC). The investigation focuses on utilizing the RRT algorithm for waypoint generation in static environments. Leveraging Particle Swarm Optimization (PSO) enhances UUV control by optimizing FLC parameters, ensuring trajectory adherence to obstacle avoidance criteria. Through diverse experimental scenarios, the efficacy of the FLC regulator has been demonstrated, particularly in 3D waypoint navigation using Line-Of-Sight (LOS) guidance, showcasing accurate waypoint navigation, precise course maintenance, and effective pitch and yaw angle control for successful destination arrival. Moreover, this study highlights the increasing importance of RANS simulations in comprehending flow dynamics. It emphasizes a CFD-centric approach for design enhancement and aims to simulate 3D turbulent flow around UUV using ANSYS CFX code. This simulation evaluates appendage effects on overall drag and their interaction with the hull, effectively characterizing hydrodynamic behavior around the defined shape, aligning with study objectives.
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    Implementation of Battery Characterization System
    (MDPI, 2023) Zermout, Abdelaziz; Belaidi, Hadjira; Maache, Ahmed
    The successful transfer toward green renewable energy depends heavily on good, reliable Energy Storage Systems (ESS). Lithium-ion batteries are the preferred choice for many applications; however, they need careful management, especially an accurate State-Of-Charge (SOC) estimation. Hence, in this paper an overview of some SOC estimation methods is briefly described; then, an automated battery cell test system prototype that will enable further improvement is designed and implemented. Some tests are conducted on an aged lithium-ion cell and the obtained results are satisfactory and accurate with an error of around 0.5 × 10−3 (V or A), thus validating the proposed prototype.
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    AC Loads Supply Continuity in Connected and Islanded Microgrids Systems
    (2023) Kaddour, Djillali; Belaidi, Hadjira; Belaidi, Dehia; Faouzi, Didi
    In the pursuit of establishing a sustainable and highly reliable microgrid, the continual operation and system dependability in both grid-connected and islanded configurations emerge as paramount objectives. Our vision centers on the implementation of an intelligent Energy Management System (EMS), complemented by cutting-edge optimization techniques and well-suitable resource sizing. These synergistic components empower the microgrid to adeptly manage peak demands, surmounting even the most adverse weather conditions, all the while liberating it from external resources or any additional draw from the grid facility. Conducting a compelling case study, we delve into the efficiency of our EMS algorithm, thoughtfully realized through MATLAB Simulink, by analyzing pertinent load profiles and power consumption data from buildings within our esteemed institution, IGEE (Institute of Electrical and Electronic Engineering). To transcend the confines of conventional grid-tied PV systems Inverter, we ingeniously propose a novel approach, coordinating a Diesel Generator-Photovoltaic panel (DG-PV) synchronization, thereby seamlessly enabling the grid-tied PV system to function in off-grid scenarios. This concept lies in achieving optimal performance through the deployment of uniform Distributed Energy Resources (DERs) sizes for Photovoltaic (PV) and Battery Energy Storage Systems (BESS) in both grid-connected and islanded modes. Supplemented by sophisticated control algorithms and real-time monitoring, the microgrid flawlessly transits between operational modes, ensuring unrivaled efficiency and unwavering dependability.
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    Enhanced quadrotor motion analysis through extended
    (SAGE, 2024) Saibi, Ali; Belaidi, Hadjira; Kobzili, Elhaouari; Demim, Fethi; Allam, Ahmed; Attouche, Nesrine; Belkacemi, Malak
    This paper aims to develop a stable quadrotor’s flight controller using the ESP32 microcontroller, enabling wireless guidance through a Graphical User Interface (GUI) on Raspberry Pi. In this context, an Extended Kalman Filter (EKF) with a nonlinear control model is employed to estimate the angular velocity and speed of the quadrotor. Simulationswere conducted using two nonlinear controllers (BackStepping Controller (BSC) and Sliding Mode Controller (SMC)) across various scenarios to prove the efficiency of the proposed method for trajectory tracking. The performance was analyzed using Root Mean Square Error (RMSE) and compared to previous works. It was noticed that in the both control scenarios, the estimated states followed the desired instructions, although a potential overshoot was noted in the case of SMC. Additionally, two control approaches were practically implemented. The first approach utilizes the classical Proportional Integral Derivative (PID) technique, while the second approach employs the modern Backstepping technique. The results demonstrate that both control approaches deliver satisfactory performance and responsiveness in stabilizing the quadrotor in real-world scenarios. However, it has been noticed that the Backstepping controller achieves higher performance, whereas, the PID controller’sperformance is constrained by tuning and model limitations.
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    Enhancing Echo Processing Through the Integration of Support Vector Machine and Weber’s Law Descriptors
    (SciTePress, 2024) Hedir, Mehdia; Demim, Fethi; Messaoui, Ali Zakaria; Messaoui, Aimen Abdelhak; Belaidi, Hadjira; Rouigueb, Abdenebi; Nemra, Abdelkrim
    Removing ground echoes from weather radar images is a topic of great importance due to their significant impact on the accuracy of processed data. To address this challenge, we aim to develop methods that effectively eliminate ground echoes while preserving the precipitation, which is a crucial meteorological parameter. To accomplish this, we propose to test Local Descriptors based on Weber’s law (WLD), as well as descriptors that combine Weber’s law with Local Binary Pattern (WLBP), using Support Vector Machine (SVM) classifiers to automate the recognition of both types of echoes. The proposed methods are rigorously tested at the sites of Setif and Bordeaux to evaluate their effectiveness in accurately identifying the ground echoes and precipitation. The results of our experiments demonstrate that the proposed techniques are highly effective in eliminating ground echoes while preserving the precipitation, and can be considered satisfactory for practical applications in meteorological data processing.
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    Online estimation of state-of-charge using auxiliary load
    (Erol Kurt, 2024) Zermout, Abdelaziz; Belaidi, Hadjira; Maache, Ahmed
    Numerous approaches and methodologies have been established for online (while the load is supplied) estimation of the State-of-Charge of Lithium-ion cells and batteries. However, as battery load consumption fluctuates in real time because of delivered device operations, obtaining a precise online state of charge estimation remains a challenging task. This work proposes a new technique for online open circuit voltage measurement to estimate state of charge of batteries. This novel technique proposes the addition of an auxiliary regulated load that may be utilized to temporarily force specifically defined forms of the battery's current curve under particular conditions, which results in improving and simplifying online open circuit voltage computations. The effectiveness of the proposed technique was successfully validated through several experimental tests. The acquired findings demonstrated its efficiency with an acceptable online state of charge estimation accuracy. Typically, an estimation error of less than 2% was recorded in most tests, while the error was less than 1% when the battery's state of charge was high.
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    Multi-microgrids system’s resilience enhancement
    (Institute of Advanced Engineering and Science (IAES), 2024) Chalah, Samira; Belaidi, Hadjira
    Nowadays, electricity consumption is increasing rapidly which leads to conventional power systems exhaustion. Therefore, micro-grids (MGs) implantation can enhance the resilience of power systems by implication of new resources, such as renewable energy sources (solar panel and wind power systems), electric vehicles (EV), and energy storage systems (ESS). This paper proposes a new strategy for optimal power consumption inside one microgrid; then, the approach will be extended to optimize the power consumption to enhance the resilience in the case of multi-MGs systems. The system controller of each microgrid has been implemented using ESP32 microcontroller and Raspberry IP4. The proposed approach intends to enhance the resilience of the system to react to any contingency in the system such as loss of power linkage between MG and the network in case of any natural disaster, especially in the rural area. Two controllers are implemented; the first one ensures MG autonomy by the efficient use of its own sources. The second one handles the system resilience cases by demanding/delivering power from/into neighbor microgrids. Hence, this work enhances the system resilience with an optimal cost. Thus, the MG can offer ancillary services for the neighboring MGs.
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    Smooth Sliding Mode Control Based Technique of an Autonomous Underwater Vehicle Based Localization Using Obstacle Avoidance Strategy
    (Science and Technology Publications, Lda, 2023) Demim, Fethi; Rouigueb, Abdenebi; Belaidi, Hadjira; Messaoui, Ali Zakaria; Bensseghieur, Khadir Lakhdar; Allam, Ahmed; Benatia, Mohamed Akram; Nouri, Abdelmadjid; Nemra, Abdelkrim
    Navigating underwater environments presents serious challenges in control and localization technology. The successful navigation of uncharted territories requires autonomous maneuvers that achieve goals while avoiding obstacles, posing a significant problem to be addressed. Detection-based control using sensor data and obstacle avoidance technology are vital for the autonomy of Autonomous Underwater Vehicles (AUVs). This study focuses on developing a control method based on Sliding Mode Control (SMC) and utilizing an imaging sonar sensor for obstacle avoidance. The proposed approach includes a controller for pitch and depth control, enabling avoidance of stationary objects. A Gaussian potential function is employed to guide the AUV’s maneuvers and avoid obstructions. Numerous simulation results evaluate the control performance of the AUV in realistic simulation conditions, assessing accuracy and stability. The experimental in simulation results demonstrate the excellent performance of our approach in navigating various obstacles such as gentle rise, steep drop-off, and underwater walls, using seafloor environment simulation models.
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    Advanced Trajectory Planning and 3D Waypoints Navigation of Unmanned Underwater Vehicles Based Fuzzy Logic Control with LOS Guidance Technique
    (Science and Technology Publications, Lda, 2023) Demim, Fethi; Belaidi, Hadjira; Rouigueb, Abdenebi; Messaoui, Ali Zakaria; Louadj, Kahina; Saghour, Sofian; Benatia, Mohamed Akram; Chergui, Mohamed; Nemra, Abdelkrim; Allam, Ahmed; Kobzili, Elhaouari
    Trajectory planning is a critical action for achieving the objectives of Unmanned Underwater Vehicles (UUVs). To navigate through complex environments, this study investigates motion trajectory planning using Rapidlyexploring Random Trees (RRT) and Fuzzy Logic Control (FLC). Our goal is to explore the use of the RRT trajectory planning algorithm to generate waypoints in a known static environment. In this case, the UUV’s planned trajectory can meet the required conditions for obstacle avoidance. By using various objective functions, the model can be solved, and the corresponding control variables can be adjusted to effectively accomplish the requirements of underwater navigation. This technique has been successfully applied in various experimental scenarios, demonstrating the effectiveness of the FLC regulator. For instance, The 3D waypoint navigation challenge has been tackled by implementing the Fuzzy Controller, which utilizes the robust Line-Of-Sight (LOS) guidance technique. Experimental results demonstrate that the FLC regulator efficiently navigates through the waypoints, maintains an accurate course, controls the pitch and yaw angles of the UUV, and successfully reaches the final destination.