Browsing by Author "Bradai, Rafik"

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Adaptive control of induction motor with unknown motor resistance
(2007) Chetate, Boukhmis; Bradai, Rafik; Kabache, Nadir
In this paper, a new approach for induction motor rotor resistance variation estimate is presented by using adaptive neural networks. Indeed, the proposed neural networks are endowed with adaptive rules that allow them to estimate the true values of the necessary nonlinear state feedbacks for the input-output feedback linearization control of an induction motor. A comparison between the nonlinear state feedbacks provided by neural networks and those calculated through the nominal model of the induction motor with nominal parameters allows us to estimate the variation in the rotor resistance
Application of the neurone – fuzzy technique for the minimisation of MF of asynchronous machine fuzzy speed regulator
(2003) Bradai, Rafik; Chetate, Boukhmis
From their early discovry, the fuzzy-neural techniques did not show enough use and interest in other fields of research as it for systems identification and diagnosis. In this paper, the application of these techniques in the control of induction machine (M.I) is presented. therefor, the fuzzy control of MI is handled. The fuzzy controlletr of 7 membership function (M.F) is used for speed control, offering the possibility of tuning its control parameters as a function of speed error. A M.F minimization of this controller is developped using fuzzy-neural technique
Commande vectorielle de la machine asynchrone associée aux onduleurs multiniveaux utilisation des régulateurs neuro-flous
(2001) Bradai, Rafik
Elaboration d’éléments optimisés de commandes vectorielles d’une machine asynchrone et leur implémentation sur un circuit à architecture reconfigurable de type FPGA
(2007) Bradai, Rafik
Dans ce travail nous proposons l’application des techniques de réseaux de neurones et des réseaux adaptatifs non-linéaires pour la conception de régulateurs à structures optimisées imitant le fonctionnement d’un régulateur flou de vitesse de la machine asynchrone. Ces régulateurs doivent assurer un contrôle de vitesse de la machine asynchrone répondant aux exigences technologiques actuelles (rapidité, efficacité et simplicité). En effet, bien que les régulateurs flous à sept fonctions d’appartenances assurent des performances statiques et dynamiques importantes lorsqu’ils sont utilisés dans les circuits de commande de la vitesse d’une machine asynchrone, ils sont complexes et sont caractérisés par une structure en série. D’autre part, l’utilisation des circuits modernes à architectures configurables permet de surmonter les contraintes liées à l’implémentation des éléments des commandes vectorielles des moteurs asynchrones. Ces circuits conviennent parfaitement à une implémentation optimale de la commande électrique, du fait qu’ils ont un coût réduit et qu’ils sont caractérisés par une grande densité d’intégration et une grande flexibilité avec une structure totalement reconfigurable. Par ailleurs, nous avons procédé à l’implémentation de la modulation à largeur d’impulsion vectorielle sur un circuit de type FPGA. L’algorithme d’implémentation proposé est basé sur la sélection des secteurs par les trois équations de base, et sur l’utilisation des dites équations pour le calcul des cycles de conductions. L’implémentation de cet algorithme a été faite à l’aide d’un outil de haut niveau ; a savoir: le System Generator de Xilinx
Enhanced power system stabilizer tuning using marine predator algorithm with comparative analysis and real time validation
(Nature Portfolio, 2024) Hattabi, Intissar; Kheldoun, Aissa; Bradai, Rafik; Khettab, Soufian; Sabo, Aliyu; Belkhier, Youcef; Khosravi, Nima; Oubelaid, Adel
This study concentrates on the implementation of Marine Predator Algorithm (MPA) scheme for tuning of a power system stabilizer’s (PSS’s) parameters to damp the low-frequency oscillations in a power system. To this, the single machine infinite bus system (SMIB), the Western System Coordinating Council (WSCC) and the New England 10 machine 39-bus power system are utilized for testing and comparing different metaheuristic algorithms using different fitness functions. Optimal PSS parameters of SMIB test system are validated using CU-SLRT Std, a real-time digital simulator. The comparative studies demonstrate that the MPA optimized PSS yields improvements of up to 98.62% in the Particle Swarm Optimization (PSO) at 69.42%, Whale Optimization Algorithm (WOA) at 71.79%, Flower Pollination Algorithm (FPA) at 72.39%, African vulture optimization algorithm (AVOA) at 78.04%, Wild Horse Optimization (WHO) algorithm at 68.57% under various operating scenarios. The superiority of the MPA optimized PSS has been validated using Hardware-in-the-loop implementation for the SMIB test system.
Experimental assessment of new fast MPPT algorithm for PV systems under non-uniform irradiance conditions
(Elsevier, 2017) Bradai, Rafik; Boukenoui, R.; Kheldoun, Aissa; Salhi, H.; Ghanes, M.; Barbot, J-P.; Mellit, A.
Guided Seagull Optimization for Improved PV MPPT in Partial Shading
(Institute of Electrical and Electronics Engineers Inc, 2023) Belmadani, Hamza; Merabet, Oussama; Obelaid, Adel; Kheldoun, Aissa; Mohit, Bajaj; Ansari, Md Fahim; Bradai, Rafik
Based on the Seagull Optimization approach, this paper proposes a completely new, rapid Maximum Power Point tracking method. After adding opposition learning and adjusting the convergence factor to the initial version, the intended algorithm - dubbed The Guided Seagull Optimizer (GSO) - was produced. Essentially, the goal of the new technique is to increase convergence speed while maintaining a reasonable global search capability. The GSO algorithm was tested on a stand-alone photovoltaic system subjected to complex multi-peak partial shadowing patterns. Overall, the findings reveal that the technique outperforms typical SOA and PSO algorithms when it comes to of convergence time, efficiency, and adaptability.
Minimum action time of a robust fuzzy speed controller for induction machine drive
(Advances in Modelling and Analysis C, 2007) Chetate, Boukhmis; Bradai, Rafik
In this paper, we propose a procedure to design an optimal fuzzy controller for indirect field oriented controlled induction machine drives. This controller has best possible performances with a minimum action time possible in a practical implementation. First, we design a fuzzy PI controller having the maximum of fuzzy sets (7 input/output membership functions), which show better static and dynamic performances. This controller is specific to speed close loop of an indirect field oriented induction machine drive. Then, in order to minimize its composition the ANFIS (Adaptive Network-Based Fuzzy Inference System) structure is applied to perform a structural and parametric optimization of this controller. We propose also, a procedure to reproduce the input/output mapping of this controller with an approximation using artificial neural networks (ANN)
A New Fast and Efficient MPPT Algorithm for Partially Shaded PV Systems Using a Hyperbolic Slime Mould Algorithm
(Wiley-Hindawi, 2024) Belmadani, Hamza; Bradai, Rafik; Kheldoun, Aissa; Mohammed, Karam Khairullah; Mekhilef, Saad; Belkhier, Youcef; Oubelaid, Adel
The design of new efficient maximum power point tracking (MPPT) techniques has become extremely important due to the rapid expansion of photovoltaic (PV) systems. Because under shading conditions the characteristics of PV devices become multimodal having several power peaks, traditional MPPT techniques provide crappy performance. In turn, metaheuristic algorithms have become massively employed as a typical substitute in maximum power point tracking. In this work, a new optimizer, which was named the hyperbolic slime mould algorithm (HSMA), is designed to be employed as an efficient MPPT algorithm. The hyperbolic tangent function is incorporated into the optimizer framework equations to scale down large perturbations in the tracking stage and boost its convergence trend. Moreover, to provide a strong exploration capability, a new mechanism has been developed in such a way the search process is carried out inside the best two power peak regions along the initial iterations. This region inspection mechanism is the prime hallmark of the designed optimizer in avoiding local power peaks and excessive global search operations. The developed algorithm was examined through diverse complicated partial shading conditions to challenge its global and local search abilities. A comparative analysis was carried out against the well-regarded PSO, GWO, and the standard slime mould algorithm. In overall, the designed optimizer defeated its contenders in all aspects offering higher efficiency, superior robustness, faster convergence, and fewer fluctuations to the operating point. An experimental setup that consists of the DSpace microcontroller and a PV emulator was employed to validate the algorithm overall performance. The recorded outcomes outline that the developed optimizer can achieve a tracking time of 0.6 seconds and 0.86 seconds on average, with 99.85% average efficiency under complex partial shading conditions.
A new golden section method-based maximum power point tracking algorithm for photovoltaic systems
(Elsevier, 2016) Kheldoun, Aissa; Bradai, Rafik; Boukenoui, R.; Mellit, A.
An optimal coordination of directional overcurrent relays using a Gorilla troops optimizer
(IEEE, 2023) Merabet, Oussama; Bouchahdane, Mohamed; Belmadani, Hamza; Kheldoun, Aissa; Eltom, Ahmed; Bradai, Rafik
The optimization of coordination of directional overcurrent relays in an interconnected power system is given in this work. The goal of protective relay coordination is to achieve selectivity while maintaining sensitivity and a fast fault clearing time. The coordination research revolves around calculating the relays’ time dial setting (TDS) and plug setting (PS). DOCR coordination is a difficult and fascinating problem in nonlinear optimization. To avoid too much breakdown and interference, the overall working duration of all necessary relays must be kept to a minimum. To solve the coordination issue at the DOCR, coordination is carried out using the Gorilla troops optimizer (GTO). IEEE 3-bus and 8-bus test systems are among the test systems to which the suggested method has been implemented. The Results collected demonstrate the suggested GTO efficiency in reducing the relay operation time for the DOCRs’ optimum cooperation
Optimized fractional order Takagi-Sugeno Fuzzy-PID power system stabilizer: An enhanced dung beetle optimization approach
(Elsevier, 2025) Hattabi, Intissar; Kheldoun, Aissa; Bradai, Rafik; Belmadani, Hamza
This paper introduces a novel Fractional Order Takagi-Sugeno Fuzzy-PID (FO-TSF-PID) controller, optimized using an enhanced Dung Beetle Optimization (EDBO) algorithm, to improve the damping of low-frequency oscillations in power systems. The controller's design involves simultaneous optimization of membership functions (MFs) and gains, enhancing performance, particularly under three-phase fault conditions. The optimization process, executed through the EDBO algorithm, is both flexible and straightforward to implement. The FO-TSF-PID controller was tested on a two-area power system subjected to three symmetrical faults. Performance evaluations demonstrated the controller's superiority over the standard Fractional Order PID (FOFPID) controller, achieving significant improvements in inter-area and local-area eigenvalues. Specifically, inter-area improvements were 87.08 % with PSO, 83.86 % with EO, 81.29 % with DBO, and 78.89 % with EDBO, while local-area improvements were 71.01 % with PSO, 70.52 % with EO, 65.73 % with DBO, and 64.32 % with EDBO. Comparative analysis against traditional controllers such as Lead-Lag Power System Stabilizer (PSS), Proportional-Integral-Derivative (PID), and Fractional Order PID (FOPID) consistently showed the FO-TSF-PID controller's enhanced stability and robustness. Further comparisons revealed that the EDBO-optimized FO-TSF-PID controller achieved 99.94 %, 99.93 %, and 99.95 % enhancements compared to those optimized using PSO, EO, and DBO, respectively. The results indicate that the EDBO-optimized FO-TSF-PID controller excels in reducing settling time, minimizing overshoot, and improving steady-state error, thus proving its efficacy in stabilizing power systems
Performance evaluation of PUC7‐based multifunction single‐phase solar active filter in real outdoor environments: Experimental insights
(John Wiley and Sons Inc, 2024) Khettab, Soufiane; Kheldoun, Aissa; Bradai, Rafik; Oubelaid, Adel; Kumar, Sandeep; Khosravi, Nima
This paper presents a novel architecture to enhance the performance of grid-connected photovoltaic (PV) systems through the introduction of several key novelties. Firstly, a packed U-cell seven-level (PUC7)-based single-phase solar active filter is implemented, offering a comprehensive solution for harmonics mitigation, reactive power compensation, and efficient power extraction from the PV source, while facilitating the injection of real power into the grid. Secondly, the p-q power injection algorithm is modified to accommodate the extraction of solar power from the PV generator to the grid, simultaneously addressing the need for harmonic current injection to improve power quality. This modification ensures dynamic performance by extracting reference current with harmonic content and solar power information, thereby enhancing the system's overall efficiency. Lastly, the proposed architecture undergoes real outdoor testing, validating its performance in various key aspects including maximum power tracking, reduction of total harmonic distortion in comparison with previous work, operation at unity power factor, and testing the effective operation of the multifunction feature. These contributions collectively demonstrate the effectiveness of the proposed system in enhancing power injection quality and reactive power compensation under real outdoor conditions of PV systems connected to the grid.
A Taguchi method-based optimization algorithm for the analysis of the wind driven-self-excited induction generator
(Institute of Advanced Engineering and Science (IAES), 2024) Boukenoui, Rachid; Bradai, Rafik; Kheldoun, Aissa
This paper investigates the use of a new global optimization algorithm that is based on Taguchi method to determine the performance parameters of self-excited induction generator being driven by variable speed wind. This analysis is based on solving equations obtained from the per-phase equivalent circuit of the induction generator. The equations have two unknowns namely the frequency and the magnetizing reactance. Both unknown are strongly dependent on the wind turbine speed, the capacity of the excitation, the load being connected at the terminals of the stator and eventually the per-phase equivalent circuit parameters. The resulting equations are nonlinear and subsequently to solve them one can employ either gradient-based algorithms or heuristic algorithms. This paper uses a new heuristic algorithm based on the Taguchi method which, in addition to its global research capability, offers superior characteristics in terms of accuracy and ease of implementation. A comparison with recently published optimization methods is carried out to show its performances in terms of accuracy and ease of implementation. The MATLAB software will be used to perform this analysis on a machine of 0.75 kW while some will be validated experimentally to confirm the aforementioned benefits.
A twofold hunting trip African vultures algorithm for the optimal extraction of photovoltaic generator model parameters
(Taylor et francis, 2022) Belmadani, Hamza; Kheldoun, Aissa; Bradai, Rafik; Bradai, Rafik; Daula Siddique, Marif
The development of reliable simulators that finely imitate the behavior of PV devices is vitally important for the design and optimization of efficient and stable photovoltaic systems. In this work, an improved variant of the African Vultures Optimization Algorithm named IAVOA is designed to serve as a powerful tool for extracting the unknown parameters of photovoltaic models. The introduced scheme incorporates a twofold strategy in such a way that allows a portion of the search agents to conduct a global search while the remaining portion performs a local search. The embedded mechanism is based on two equations added to the standard version, and by which the exploration and exploitation capabilities of the algorithm have significantly been fostered. To testify the performance of the IAVOA, a comparative study based on the Root Mean Square Error (RMSE), was conducted on six distinct benchmark PV models, and the obtained results were, in most cases, remarkably superior to the ones achieved by its competitors. The algorithm was able to produce values for the ideality factors that have not been previously found by any existing work to the best of our knowledge. In turn, the Double Diode and Triple Diode models’ accuracies were notably improved with RMSE scores of 6.9096×10−4 and 7.4011×10−4 respectively for the RTC France cell, and 1.4251×10−2 for the STP6-120/36 module, outperforming the existing techniques. In light of that, it can be reliably presumed that the IAVOA is indeed a promising algorithm for the electrical characterization of PV devices.