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Abdeljalil El Kari
LSET, Department of Applied Physics, Faculty of Science and Technology Gueliz, Cadi Ayyad University, Marrakech 40000, Morocco

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Journal article
Published: 29 April 2019 in Applied Sciences
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This paper deals with the trajectory tracking problem for a quadrotor unmanned aerial vehicle (UAV). For this purpose, two control strategies are proposed. First, a flight controller with a hierarchical structure is designed, whereby the complete closed-loop system is divided into two blocks. The system has an inner block for attitude control and an outer block for position stabilization, for a total of six proportional-derivative/proportional-integral-derivative (PD/PID) controllers. The second new trajectory tracking strategy is based on attitude stabilization. In addition to a direct stabilization of yaw and altitude, the x and y positions are stabilized by choosing an appropriate control of roll and pitch angles. The relations between positions (x, y) and rotations (roll, pitch) are derived from the natural flight of the quadcopter. In this second approach, with only four controllers, the quadrotor UAV is able to follow any trajectory. In both approaches, the PD/PID controllers are synthesized using the genetic algorithm method, and compared with those obtained by the reference model method. Furthermore, a comparison between PD and PID controller performance is performed. Thereafter, the robustness of the proposed controllers is tested for trajectory tracking in a disturbed environment. Simulation results demonstrate that for the two approaches, PD controllers show a better behavior with respect to quadcopter stabilization than in trajectory tracking under different conditions.

ACS Style

Imane Siti; Mostafa Mjahed; Hassan Ayad; Abdeljalil El Kari. New Trajectory Tracking Approach for a Quadcopter Using Genetic Algorithm and Reference Model Methods. Applied Sciences 2019, 9, 1780 .

AMA Style

Imane Siti, Mostafa Mjahed, Hassan Ayad, Abdeljalil El Kari. New Trajectory Tracking Approach for a Quadcopter Using Genetic Algorithm and Reference Model Methods. Applied Sciences. 2019; 9 (9):1780.

Chicago/Turabian Style

Imane Siti; Mostafa Mjahed; Hassan Ayad; Abdeljalil El Kari. 2019. "New Trajectory Tracking Approach for a Quadcopter Using Genetic Algorithm and Reference Model Methods." Applied Sciences 9, no. 9: 1780.

Journal article
Published: 25 April 2019 in Applied Sciences
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This paper explores the full control of a quadrotor Unmanned Aerial Vehicles (UAVs) byexploiting the nature-inspired algorithms of Particle Swarm Optimization (PSO), Cuckoo Search(CS), and the cooperative Particle Swarm Optimization-Cuckoo Search (PSO-CS). The proposedPSO-CS algorithm combines the ability of social thinking in PSO with the local search capability inCS, which helps to overcome the problem of low convergence speed of CS. First, the quadrotordynamic modeling is defined using Newton-Euler formalism. Second, PID (Proportional, Integral,and Derivative) controllers are optimized by using the intelligent proposed approaches and theclassical method of Reference Model (RM) for quadrotor full control. Finally, simulation resultsprove that PSO and PSO-CS are more efficient in tuning of optimal parameters for the quadrotorcontrol. Indeed, the ability of PSO and PSO-CS to track the imposed trajectories is well seen from3D path tracking simulations and even in presence of wind disturbances.

ACS Style

Nada El Gmili; Mostafa Mjahed; Abdeljalil El Kari; Hassan Ayad; El Gmili; El Kari; Ayad. Particle Swarm Optimization and Cuckoo Search-Based Approaches for Quadrotor Control and Trajectory Tracking. Applied Sciences 2019, 9, 1719 .

AMA Style

Nada El Gmili, Mostafa Mjahed, Abdeljalil El Kari, Hassan Ayad, El Gmili, El Kari, Ayad. Particle Swarm Optimization and Cuckoo Search-Based Approaches for Quadrotor Control and Trajectory Tracking. Applied Sciences. 2019; 9 (8):1719.

Chicago/Turabian Style

Nada El Gmili; Mostafa Mjahed; Abdeljalil El Kari; Hassan Ayad; El Gmili; El Kari; Ayad. 2019. "Particle Swarm Optimization and Cuckoo Search-Based Approaches for Quadrotor Control and Trajectory Tracking." Applied Sciences 9, no. 8: 1719.

Chapter
Published: 25 December 2018 in Smart and Sustainable Planning for Cities and Regions
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This chapter presents a detailed procedure to study and discuss the behavior of different maximum power point tracking (MPPT) techniques applied to PV systems. In this work, we presented a review on the state-of-the-art of photovoltaic System, DC/DC converter and power point tracking techniques such as conventional one incremental conductance (INC) and soft computing method fuzzy logic controller (FLC) are evaluated. The simulation results obtained are developed under software MATLAB/Simulink. Both methods (INC) and (FLC) are used with a boost DC/DC converter and a load. These results show that the fuzzy logic controller is better and faster than the conventional incremental conductance (INC) technique in both dynamic response and steady state in normal operation.

ACS Style

Aouatif Ibnelouad; Abdeljalil El Kari; Hassan Ayad; Mostafa Mjahed. A Comprehensive Comparison of Two Behavior MPPT Techniques, the Conventional (Incremental Conductance (INC)) and Intelligent (Fuzzy Logic Controller (FLC)) for Photovoltaic Systems. Smart and Sustainable Planning for Cities and Regions 2018, 47 -84.

AMA Style

Aouatif Ibnelouad, Abdeljalil El Kari, Hassan Ayad, Mostafa Mjahed. A Comprehensive Comparison of Two Behavior MPPT Techniques, the Conventional (Incremental Conductance (INC)) and Intelligent (Fuzzy Logic Controller (FLC)) for Photovoltaic Systems. Smart and Sustainable Planning for Cities and Regions. 2018; ():47-84.

Chicago/Turabian Style

Aouatif Ibnelouad; Abdeljalil El Kari; Hassan Ayad; Mostafa Mjahed. 2018. "A Comprehensive Comparison of Two Behavior MPPT Techniques, the Conventional (Incremental Conductance (INC)) and Intelligent (Fuzzy Logic Controller (FLC)) for Photovoltaic Systems." Smart and Sustainable Planning for Cities and Regions , no. : 47-84.

Journal article
Published: 14 November 2018 in Applied Sciences
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Monitoring and diagnosis of rotating machines has become an effective and indispensable tool for the efficient and timely detection of defects, avoiding then incidents that can have serious economic and human consequences. Bearings are the most sensitive parts of these machines; this is why special attention must be paid to its monitoring. This paper presents a methodology for diagnosing an aircraft air compressor bearing using neural networks that have been optimized by genetic algorithms. We used in our study a database of vibratory signals that were recorded on a test bench from bearings with different defects. The faults features are extracted from these noisy signals using the estimate of the spectral density. The diagnostic capacity of obtained model has been demonstrated by a comparative study with two other automatic classifiers, which are discriminant analysis and neural networks whose training has been done with the Back-Propagation algorithm. This approach has the advantage of simultaneously ensuring the optimal structure of the neural network and accomplishing its learning. The importance of this study is the construction of a diagnostic tool that is characterized by efficiency, speed of decision making and ease of implementation not only on the computers on the ground, but also on the mounted calculators on aircraft.

ACS Style

Ahmed Youssef Ouadine; Mostafa Mjahed; Hassan Ayad; Abdeljalil El Kari. Aircraft Air Compressor Bearing Diagnosis Using Discriminant Analysis and Cooperative Genetic Algorithm and Neural Network Approaches. Applied Sciences 2018, 8, 2243 .

AMA Style

Ahmed Youssef Ouadine, Mostafa Mjahed, Hassan Ayad, Abdeljalil El Kari. Aircraft Air Compressor Bearing Diagnosis Using Discriminant Analysis and Cooperative Genetic Algorithm and Neural Network Approaches. Applied Sciences. 2018; 8 (11):2243.

Chicago/Turabian Style

Ahmed Youssef Ouadine; Mostafa Mjahed; Hassan Ayad; Abdeljalil El Kari. 2018. "Aircraft Air Compressor Bearing Diagnosis Using Discriminant Analysis and Cooperative Genetic Algorithm and Neural Network Approaches." Applied Sciences 8, no. 11: 2243.

Journal article
Published: 30 October 2018 in Aerospace
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In this study, we develop a rigorous tracking control approach for quadrotor unmanned aerial vehicles (UAVs) with unknown dynamics, unknown physical parameters, and subject to unknown and unpredictable disturbances. In order to better estimate the unknown functions, seven interval type-2-adaptive fuzzy systems (IT2-AFSs) and five adaptive systems are designed. Then, a new IT2 adaptive fuzzy reaching sliding mode system (IT2-AFRSMS) which generates an optimal smooth adaptive fuzzy reaching sliding mode control law (AFRSMCL) using IT2-AFSs is introduced. The AFRSMCL is designed a way that ensures that its gains are efficiently estimated. Thus, the global proposed control law can effectively achieve the predetermined performances of the tracking control while simultaneously avoiding the chattering phenomenon, despite the approximation errors and all disturbances acting on the quadrotor dynamics. The adaptation laws are designed by utilizing the stability analysis of Lyapunov. A simulation example is used to validate the robustness and effectiveness of the proposed method of control. The obtained results confirm the results of the mathematical analysis in guaranteeing the tracking convergence and stability of the closed loop dynamics despite the unknown dynamics, unknown disturbances, and unknown physical parameters of the controlled system.

ACS Style

Nabil Nafia; Abdeljalil El Kari; Hassan Ayad; Mostafa Mjahed. Robust Full Tracking Control Design of Disturbed Quadrotor UAVs with Unknown Dynamics. Aerospace 2018, 5, 115 .

AMA Style

Nabil Nafia, Abdeljalil El Kari, Hassan Ayad, Mostafa Mjahed. Robust Full Tracking Control Design of Disturbed Quadrotor UAVs with Unknown Dynamics. Aerospace. 2018; 5 (4):115.

Chicago/Turabian Style

Nabil Nafia; Abdeljalil El Kari; Hassan Ayad; Mostafa Mjahed. 2018. "Robust Full Tracking Control Design of Disturbed Quadrotor UAVs with Unknown Dynamics." Aerospace 5, no. 4: 115.

Journal article
Published: 31 May 2018 in International Review of Automatic Control (IREACO)
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The aim of this paper is to optimize the performance of a Quadcopter by designing neural and fuzzy controllers. After modeling the Quadcopter dynamics using the Newton Euler formalism, three intelligent controllers are suggested. Firstly, four Reference Model based Neural Networks (RMNN) are used to stabilize three attitudes (roll, pitch, and yaw) and the altitude displacement. In this case, each neural controller first learns to provide a control law allowing the Quadcopter to follow a chosen Reference Model. Taking into account the four flight parameters above, we will attempt in the second approach to replace four Cooperative PDs with four Neural Networks (CPDNN) whereby each Neural Network mimics the behavior of a PD controller. The third approach includes Fuzzy logic to adjust PID controllers’ gains. Finally, disturbances were taken into account to test the robustness of the controllers. Simulation results confirm the effectiveness of the proposed methods. Copyright © 2018 Praise Worthy Prize - All rights reserved.

ACS Style

Khadija EL Hamidi; Mostafa Mjahed; Abdeljalil El Kari; Hassan Ayad. Neural and Fuzzy Based Nonlinear Flight Control for an Unmanned Quadcopter. International Review of Automatic Control (IREACO) 2018, 11, 98 .

AMA Style

Khadija EL Hamidi, Mostafa Mjahed, Abdeljalil El Kari, Hassan Ayad. Neural and Fuzzy Based Nonlinear Flight Control for an Unmanned Quadcopter. International Review of Automatic Control (IREACO). 2018; 11 (3):98.

Chicago/Turabian Style

Khadija EL Hamidi; Mostafa Mjahed; Abdeljalil El Kari; Hassan Ayad. 2018. "Neural and Fuzzy Based Nonlinear Flight Control for an Unmanned Quadcopter." International Review of Automatic Control (IREACO) 11, no. 3: 98.

Regular paper
Published: 03 April 2018 in Automatika
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In this paper, in order to achieve the best tracking control of a class of multi-input multi-output (MIMO) nonlinear systems with unknown dynamics and unknown disturbances, a new robust adaptive interval type-2 fuzzy sliding mode control law (AIT2-FSMCL) has been proposed. Based on developing interval type-2 fuzzy local models for some operating points of the controlled system, an interval type-2 fuzzy logic system (IT2-FLS) has been designed to better estimate the unknown nonlinear dynamics of the studied system. Then, to enhance the tracking control performance and ensure the system robustness in the presence of approximation errors, parameter variations, un-modelled dynamics and external disturbances, a new AIT2-fuzzy sliding mode system (AIT2-FSMS), has been introduced. In order to avoid the chattering phenomenon while keeping the system performance, the AIT2-FSMS uses three AIT2-fuzzy logic systems (AIT2-FLSs) to estimate the optimal gains of the AIT2-FSMCL. The adaptation laws have been derived using the Lyapunov stability approach. The mathematical proof shows that the closed-loop system with the proposed control approach is globally asymptotically stable. Finally, the proposed design method is applied to a two-link robot arm to validate the effectiveness of the proposed control approach.

ACS Style

Nabil Nafia; Abdeljalil El Kari; Hassan Ayad; Mostafa Mjahed. A robust type-2 fuzzy sliding mode controller for disturbed MIMO nonlinear systems with unknown dynamics. Automatika 2018, 59, 194 -207.

AMA Style

Nabil Nafia, Abdeljalil El Kari, Hassan Ayad, Mostafa Mjahed. A robust type-2 fuzzy sliding mode controller for disturbed MIMO nonlinear systems with unknown dynamics. Automatika. 2018; 59 (2):194-207.

Chicago/Turabian Style

Nabil Nafia; Abdeljalil El Kari; Hassan Ayad; Mostafa Mjahed. 2018. "A robust type-2 fuzzy sliding mode controller for disturbed MIMO nonlinear systems with unknown dynamics." Automatika 59, no. 2: 194-207.

Conference paper
Published: 21 March 2018 in Inventive Computation and Information Technologies
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The present paper proposes a comparison between two control methods for maximum power point tracking (MPPT) of a photovoltaic (PV) system under varying irradiation and temperature conditions: the fuzzy control method and the neural networks control method. The results of simulation obtained have been developed and analyzed by using Matlab/Simulink software for the both techniques have. The power transitions at varying irradiation and temperature conditions are observed and the power tracking time appreciated by the neural networks controller against the fuzzy logic controller has been evaluated.

ACS Style

Aouatif Ibnelouad; Abdeljalil El Kari; Hassan Ayad; Mostafa Mjahed. Comparison of Fuzzy and Neural Networks Controller for MPPT of Photovoltaic Modules. Inventive Computation and Information Technologies 2018, 515 -527.

AMA Style

Aouatif Ibnelouad, Abdeljalil El Kari, Hassan Ayad, Mostafa Mjahed. Comparison of Fuzzy and Neural Networks Controller for MPPT of Photovoltaic Modules. Inventive Computation and Information Technologies. 2018; ():515-527.

Chicago/Turabian Style

Aouatif Ibnelouad; Abdeljalil El Kari; Hassan Ayad; Mostafa Mjahed. 2018. "Comparison of Fuzzy and Neural Networks Controller for MPPT of Photovoltaic Modules." Inventive Computation and Information Technologies , no. : 515-527.

Journal article
Published: 01 January 2018 in International Journal of Intelligent Engineering Informatics
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ACS Style

Abdeljalil El Kari; Hassan Ayad; Mostafa Mjahed; Nada El Gmili. Intelligent PSO-based PDs/PIDs controllers for an unmanned quadrotor. International Journal of Intelligent Engineering Informatics 2018, 6, 548 .

AMA Style

Abdeljalil El Kari, Hassan Ayad, Mostafa Mjahed, Nada El Gmili. Intelligent PSO-based PDs/PIDs controllers for an unmanned quadrotor. International Journal of Intelligent Engineering Informatics. 2018; 6 (6):548.

Chicago/Turabian Style

Abdeljalil El Kari; Hassan Ayad; Mostafa Mjahed; Nada El Gmili. 2018. "Intelligent PSO-based PDs/PIDs controllers for an unmanned quadrotor." International Journal of Intelligent Engineering Informatics 6, no. 6: 548.

Journal article
Published: 01 January 2018 in International Journal of Intelligent Engineering Informatics
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This paper presents intelligent PDs/PIDs controllers based on particle swarm optimisation (PSO) for an unmanned aerial vehicle (UAV) quadrotor. Because of physical effect, the aircraft dynamics' nature is fully coupled and strongly nonlinear. Firstly, the mathematical model is derived using Newton-Euler formalism. Based on this model, a nonlinear control scheme, incorporating six PDs/PIDs controllers, is developed to control the position (

ACS Style

Nada El Gmili; Mostafa Mjahed; Abdeljalil El Kari; Hassan Ayad. Intelligent PSO-based PDs/PIDs controllers for an unmanned quadrotor. International Journal of Intelligent Engineering Informatics 2018, 6, 548 .

AMA Style

Nada El Gmili, Mostafa Mjahed, Abdeljalil El Kari, Hassan Ayad. Intelligent PSO-based PDs/PIDs controllers for an unmanned quadrotor. International Journal of Intelligent Engineering Informatics. 2018; 6 (6):548.

Chicago/Turabian Style

Nada El Gmili; Mostafa Mjahed; Abdeljalil El Kari; Hassan Ayad. 2018. "Intelligent PSO-based PDs/PIDs controllers for an unmanned quadrotor." International Journal of Intelligent Engineering Informatics 6, no. 6: 548.

Journal article
Published: 28 February 2017 in International Review on Modelling and Simulations (IREMOS)
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ACS Style

Badr Elkari; Hassan Ayad; Abdeljalil El Kari; Mostafa Mjahed. VLSI Implementation of an Adaptable Localization System for All Unicycle Robot Platforms. International Review on Modelling and Simulations (IREMOS) 2017, 10, 8 .

AMA Style

Badr Elkari, Hassan Ayad, Abdeljalil El Kari, Mostafa Mjahed. VLSI Implementation of an Adaptable Localization System for All Unicycle Robot Platforms. International Review on Modelling and Simulations (IREMOS). 2017; 10 (1):8.

Chicago/Turabian Style

Badr Elkari; Hassan Ayad; Abdeljalil El Kari; Mostafa Mjahed. 2017. "VLSI Implementation of an Adaptable Localization System for All Unicycle Robot Platforms." International Review on Modelling and Simulations (IREMOS) 10, no. 1: 8.

Journal article
Published: 31 January 2017 in International Review of Automatic Control (IREACO)
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ACS Style

Badr Elkari; Hassan Ayad; Abdeljalil El Kari; Mostafa Mjahed. A New Approach of Fusion Behavior-Based Fuzzy Control for Mobile Robot Navigation. International Review of Automatic Control (IREACO) 2017, 10, 13 .

AMA Style

Badr Elkari, Hassan Ayad, Abdeljalil El Kari, Mostafa Mjahed. A New Approach of Fusion Behavior-Based Fuzzy Control for Mobile Robot Navigation. International Review of Automatic Control (IREACO). 2017; 10 (1):13.

Chicago/Turabian Style

Badr Elkari; Hassan Ayad; Abdeljalil El Kari; Mostafa Mjahed. 2017. "A New Approach of Fusion Behavior-Based Fuzzy Control for Mobile Robot Navigation." International Review of Automatic Control (IREACO) 10, no. 1: 13.