Papers by Yassine ABDESSEMED
Pattern Recognition in Computer Integrated Manufacturing
from a high resolution 3D range sensor. After registration between the cloud of points and the ST... more from a high resolution 3D range sensor. After registration between the cloud of points and the STL CAD model, the cloud is segmented by computing the minimal distance and compared to some local geometric properties between the 3D points and the NURBS surfaces. Controlled results are displayed in two ways: visually, using a colour map to display the level of discrepancy between the measured points and the CAD model, and a hardcopy report of the evaluation results of the tolerance specifications. The computing times are 2 seconds for a model STL made up of 15000 triangles put in correspondence with an image made up of 20000 points and about 10 seconds for the same image put in register with the same object represented with its model NURBS. K e y w o r d s: vision system, segmentation, pattern recognition, inspection 1
A robust synergetic controller for Quadrotor obstacle avoidance using Bézier curve versus B-spline trajectory generation
Intell. Serv. Robotics, 2022
This paper deals with a robust synergetic controller for planning an optimal trajectory and a gui... more This paper deals with a robust synergetic controller for planning an optimal trajectory and a guidance of the Quadrotor in complex environment. The Bézier curve method is introduced to plan the path of the Quadrotor, where the control points will be generated automatically to avoid the collusion with anything, keeping a high accuracy to detect the obstacles. In addition, the B-spline curves are generated in order to compare the proposed approach performances. Furthermore, a synergetic controller is synthesized for the attitude control of the Quadrotor, and the stability analysis of the proposed method is formally established. Numerical simulations are presented in order to show the effectiveness of the proposed controller. Experimental validation through a Quadrotor test bench is given in order to confirm the reported theoretical results.
A New Approach to Beacons Detection for a Mobile Robot Using a Neural Network Model
Abstract: In this paper we propose a neuro-mimetic technique relating to the detection of beacons... more Abstract: In this paper we propose a neuro-mimetic technique relating to the detection of beacons in mobile robotics. The objective is to bring a robot moving in an unspecified environment to acquire attributes for recognition. We develop a practical approach for the segmentation of images of objects of a scene and evaluate the performances in real time of them. The neuronal classifier used is a window of a network MLP (9-6-3-1) using the Algorithm of retro-propagation of the gradient, where the distributed central pixel uses information in level of gray. The originality of the work lies in the use of the association of an enhanced neural network configuration and Standard Hough Transform. The results obtained with a momentum of 0.03 and one coefficient of training equal to 0.002 shows that our system is robust with an extremely appreciable computing time. ¶
In this paper a new approach to an automatic controlled system of manufactured parts is suggested... more In this paper a new approach to an automatic controlled system of manufactured parts is suggested. Inputs of the system are: an unordered cloud of 3D points of the part and its CAD model in IGES and STL formats. The 3D cloud is obtained from a high resolution 3D range sensor. After registration between the cloud of points and the STL CAD model, the cloud is segmented by computing the minimal distance and compared to some local geometric properties between the 3D points and the NURBS surfaces. Controlled results are displayed in two ways: visually, using a colour map to display the level of discrepancy between the measured points and the CAD model, and a hardcopy report of the evaluation results of the tolerance specifications. The computing times are 2 seconds for a model STL made up of 15000 triangles put in correspondence with an image made up of 20000 points and about 10 seconds for the same image put in register with the same object represented with its model NURBS.
Tracking power photovoltaic system with a fuzzy logic control strategy
2014 6th International Conference on Computer Science and Information Technology (CSIT), 2014
ABSTRACT Photovoltaic generation is the technique which uses photovoltaic cell to convert solar e... more ABSTRACT Photovoltaic generation is the technique which uses photovoltaic cell to convert solar energy to electric energy. Nowadays, PV generation is developing increasingly fast as a renewable energy source. However, the disadvantage is that PV generation is intermittent for depending on weather conditions. This paper proposes an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and solar radiation conditions. This method uses a fuzzy logic controller applied to a DC-DC boost converter device. A photovoltaic system including a solar panel, a DC-DC converter, a Fuzzy MPP tracker and a resistive load is modeled and simulated. Finally performance comparison between fuzzy logic controller and Perturb and Observe method has been carried out which has shown the effectiveness of fuzzy logic controller to draw much energy and fast response against change in working conditions.
International Journal of Computer Applications, 2013
In this paper a new maximum-power-point-tracking (MPPT) controller for a photovoltaic (PV) energy... more In this paper a new maximum-power-point-tracking (MPPT) controller for a photovoltaic (PV) energy conversion system is proposed. Nowadays, PV generation is more and more used as a renewable energy source. However, its main drawback is that PV generation is intermittent because it depends on shading conditions consequently irradiance value. Thus, the MPPT (Maximum Power Point Tracking Technique) together with the battery energy storage is necessary in order to obtain a stable and reliable maximum output power from a PV generation system. In our research work, the reference voltage for the MPPT is obtained by an artificial neural network (ANN) using the steepest negative gradient algorithm. The tracking algorithm adjusts the duty-cycle value of the dc/dc buck converter so that the PV-module voltage equals the voltage corresponding to the MPPT for any given realistic operation irradiance and temperature. The controller, which uses the classical perturb and observe (P&O) technique processes then the information gathered to a ANN controller bloc, which in turn generates the optimal value of the buck converter duty-cycle. The energy obtained from the converter is stored in a lithium-ion battery which feeds a useful load. The simulation results show the effectiveness of this method for the extraction of the maximum power available in the presence of different types of disturbances.
International Journal of Electrical and Computer Engineering (IJECE), 2016
This paper presents an intelligent control strategy that uses a feedforward artificial neural net... more This paper presents an intelligent control strategy that uses a feedforward artificial neural network in order to improve the performance of the MPPT (Maximum Power Point Tracker) photovoltaic (PV) power system based on a modified Cuk converter. The proposed neural network control (NNC) strategy is designed to produce regulated variable DC output voltage. The mathematical model of the Cuk converter is developed and an artificial neural network algorithm is derived. The Cuk converter has some advantages compared to other types of power converters. However the nonlinear characteristic of the Cuk converter due to the required switching technique is difficult to be handled by conventional controller. To overcome this problem, a neural network controller with online learning back propagation algorithm is elaborated. The designed NNC strategy tracks the converter voltage output changes and improves the system dynamic performance regardless of the load disturbances and supply variations. The proposed controller effectiveness during dynamic transient response is then analyzed and verified using MATLAB-Simulink. The simulation results confirm the excellent performance of the proposed NNC technique for the studied PV system.
Automatika ‒ Journal for Control, Measurement, Electronics, Computing and Communications, 2016
Original scientific paper In this paper, a simulation study of the maximum power point tracking (... more Original scientific paper In this paper, a simulation study of the maximum power point tracking (MPPT) for a photovoltaic system using an artificial neural network is presented. Maximum power point tracking (MPPT) plays an important role in photovoltaic systems because it maximizes the power output from a PV solar system for all temperature and irradiation conditions, and therefore maximizes the power efficiency. Since the maximum power point (MPP) varies, based on the PV irradiation and temperature, appropriate algorithms must be utilized to track it in order maintain the optimal operation of the system. The software Matlab/Simulink is used to develop the model of PV solar system MPPT controller. The system simulation is elaborated by combining the models established of solar PV module and a DC/DC Boost converter. The system is studied using various irradiance shading conditions. Simulation results show that the photovoltaic simulation system tracks optimally the maximum power point even under severe disturbances conditions.
1) boutarfahal@yahoo.fr, (1) maayamahfoud@yahoo.fr, (1) ramakhloufi@yahoo.fr, (1) yabdes@yahoo.fr... more 1) boutarfahal@yahoo.fr, (1) maayamahfoud@yahoo.fr, (1) ramakhloufi@yahoo.fr, (1) yabdes@yahoo.fr, (1) bougnour@yahoo.fr, (2) emptoz@rfv-lyon.fr Abstract: In this paper we propose a neuro-mimetic technique relating to the detection of beacons in mobile robotics. The objective is to bring a robot moving in an unspecified environment to acquire attributes for recognition. We develop a practical approach for the segmentation of images of objects of a scene and evaluate the performances in real time of them. The neuronal classifier used is a window of a network MLP (9-6-3-1) using the Algorithm of retro-propagation of the gradient, where the distributed central pixel uses information in level of gray. The originality of the work lies in the use of the association of an enhanced neural network configuration and Standard Hough Transform. The results obtained with a momentum of 0.03 and one coefficient of training equal to 0.002 shows that our system is robust with an extremely appreciable...
The application of GTO thyristor in PWM variable-speed AC drives
Thesis (Ph. D.)--University of Bristol, 1990.
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Papers by Yassine ABDESSEMED