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    <link>http://repository.enp.edu.dz/jspui/handle/123456789/144</link>
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    <pubDate>Wed, 08 Apr 2026 00:14:26 GMT</pubDate>
    <dc:date>2026-04-08T00:14:26Z</dc:date>
    <item>
      <title>Fractional-Order Adaptive Control Techniques for Artificial Pancreas</title>
      <link>http://repository.enp.edu.dz/jspui/handle/123456789/11362</link>
      <description>Title: Fractional-Order Adaptive Control Techniques for Artificial Pancreas
Authors: BENSALEM, Serine; Bensalem, Serine
Abstract: Type 1 diabetes mellitus is a disease where the patient is not able to produce necessary insulin&#xD;
to regulate the concentration of glucose in the blood. Artificial pancreas is a device that can&#xD;
regulate this concentration and turn the behavior to normal. The human regulatory system can&#xD;
be modeled using differential equations; their order could be integer or fractional. In this work,&#xD;
we examine the accuracy of fractional-order modeling of the minimal model using real data, then&#xD;
robust control techniques are implemented. First, a model reference indirect adaptive controller&#xD;
is designed using two approaches: integer order approach and fractional-order approach, then a&#xD;
fractional-order sliding mode controller is implemented with a robust sliding mode observer to&#xD;
estimate the glucose concentration in the blood. The controller is tuned by a genetic optimization&#xD;
algorithm. Finally, a Neuro fuzzy controller. Several robustness tests are presented (Meal&#xD;
simulation) and evaluated using different types of errors’ criteria.
Description: Mémoire de Projet de Fin d’Études :Automatique : Alger, École Nationale Polytechnique : 2025</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
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      <dc:date>2025-01-01T00:00:00Z</dc:date>
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    <item>
      <title>Icing Detection, State Estimation, and Control of Fixed-Wing Drones</title>
      <link>http://repository.enp.edu.dz/jspui/handle/123456789/11361</link>
      <description>Title: Icing Detection, State Estimation, and Control of Fixed-Wing Drones
Authors: Chaabeni, Ilyes; Boulassel, Bilel
Abstract: Reliable operation of unmanned aerial vehicles (UAVs) in uncertain and adverse conditions&#xD;
&#xD;
remains a critical challenge, particularly in the presence of icing, disturbances, and dynamic in-&#xD;
teractions in multi-agent systems. This thesis develops an integrated framework that combines&#xD;
&#xD;
probabilistic estimation and nonlinear control strategies to enhance performance and robust-&#xD;
ness. An approach based on the particle filter (PF) is employed to improve state estimation ac-&#xD;
curacy and detect icing-related faults by analyzing variations in system parameters. For robust&#xD;
&#xD;
trajectory tracking in uncertain flight conditions, the proposed control scheme combines a high-order sliding mode observer (HOSMO) with the super-twisting algorithms (STA), effectively&#xD;
managing disturbances and model variations. At the multi-agent level, a distributed control&#xD;
strategy is introduced, utilizing finite-time observers and controllers within a leader–follower&#xD;
&#xD;
structure to enable fast and coordinated group behavior. The thesis demonstrates the effec-&#xD;
tiveness of the proposed methods in enhancing fault detection capabilities, control robustness,&#xD;
&#xD;
and ensuring reliable multi-UAV coordination.
Description: Mémoire de Projet de Fin d’Études : Automatique : Alger, École Nationale Polytechnique : 2025.-Mémoire confidentiel 2ans jusqu'à Juin 2027</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://repository.enp.edu.dz/jspui/handle/123456789/11361</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Fractional-Order Control of a Helicopter Flight Simulator (TRMS): Simulation and Experimentation</title>
      <link>http://repository.enp.edu.dz/jspui/handle/123456789/11230</link>
      <description>Title: Fractional-Order Control of a Helicopter Flight Simulator (TRMS): Simulation and Experimentation
Authors: Zerrougui, Yahya Moundher; Debache, Mounsef
Abstract: This project focuses on designing and optimizing fractional-order controllers for the Twin Rotor&#xD;
MIMO System (TRMS), a nonlinear and strongly coupled platform. Two strategies—FOPID&#xD;
and FOSMC—are developed and tuned using Particle Swarm Optimization (PSO). Simulation&#xD;
results show that fractional-order controllers offer superior performance over classical methods&#xD;
in terms of robustness, disturbance rejection, and handling system nonlinearities.
Description: Mémoire de Projet de Fin d’Études :Automatique: Alger, École Nationale Polytechnique :2025</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://repository.enp.edu.dz/jspui/handle/123456789/11230</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Modeling, Identification and Control Strategies for a Reverse Osmosis-Based  Desalination System</title>
      <link>http://repository.enp.edu.dz/jspui/handle/123456789/11219</link>
      <description>Title: Modeling, Identification and Control Strategies for a Reverse Osmosis-Based  Desalination System
Authors: Guendouz, Khaled; Benseddik, Akram
Abstract: This thesis focuses on the modeling, identification, and control of a reverse osmosis (RO) desalination&#xD;
system. In response to the growing scarcity of freshwater resources, RO technology offers a&#xD;
viable and sustainable solution. The first phase involves the development of a dynamic model&#xD;
based on experimental data, accurately capturing the interactions between key variables such as&#xD;
feed pressure, pH, permeate flow rate, and conductivity. Two control strategies are explored :&#xD;
Model Predictive Control (MPC), implemented on both decoupled and multivariable models,&#xD;
and classical PID control, including an improved IMC-PID version. The results obtained highlight&#xD;
the performance, robustness, and limitations of each control approach under model uncertainties
Description: Mémoire de Projet de Fin d’Études:Automatique: Alger, École Nationale Polytechnique : 2025</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://repository.enp.edu.dz/jspui/handle/123456789/11219</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
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