http://repository.enp.edu.dz/jspui/handle/123456789/144 Tue, 07 Apr 2026 08:28:38 GMT 2026-04-07T08:28:38Z http://repository.enp.edu.dz/jspui/handle/123456789/11362 Fractional-Order Adaptive Control Techniques for Artificial Pancreas BENSALEM, Serine; Bensalem, Serine Type 1 diabetes mellitus is a disease where the patient is not able to produce necessary insulin to regulate the concentration of glucose in the blood. Artificial pancreas is a device that can regulate this concentration and turn the behavior to normal. The human regulatory system can be modeled using differential equations; their order could be integer or fractional. In this work, we examine the accuracy of fractional-order modeling of the minimal model using real data, then robust control techniques are implemented. First, a model reference indirect adaptive controller is designed using two approaches: integer order approach and fractional-order approach, then a fractional-order sliding mode controller is implemented with a robust sliding mode observer to estimate the glucose concentration in the blood. The controller is tuned by a genetic optimization algorithm. Finally, a Neuro fuzzy controller. Several robustness tests are presented (Meal simulation) and evaluated using different types of errors’ criteria. Mémoire de Projet de Fin d’Études :Automatique : Alger, École Nationale Polytechnique : 2025 Wed, 01 Jan 2025 00:00:00 GMT http://repository.enp.edu.dz/jspui/handle/123456789/11362 2025-01-01T00:00:00Z http://repository.enp.edu.dz/jspui/handle/123456789/11361 Icing Detection, State Estimation, and Control of Fixed-Wing Drones Chaabeni, Ilyes; Boulassel, Bilel Reliable operation of unmanned aerial vehicles (UAVs) in uncertain and adverse conditions remains a critical challenge, particularly in the presence of icing, disturbances, and dynamic in- teractions in multi-agent systems. This thesis develops an integrated framework that combines probabilistic estimation and nonlinear control strategies to enhance performance and robust- ness. An approach based on the particle filter (PF) is employed to improve state estimation ac- curacy and detect icing-related faults by analyzing variations in system parameters. For robust 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 managing disturbances and model variations. At the multi-agent level, a distributed control strategy is introduced, utilizing finite-time observers and controllers within a leader–follower structure to enable fast and coordinated group behavior. The thesis demonstrates the effec- tiveness of the proposed methods in enhancing fault detection capabilities, control robustness, and ensuring reliable multi-UAV coordination. Mémoire de Projet de Fin d’Études : Automatique : Alger, École Nationale Polytechnique : 2025.-Mémoire confidentiel 2ans jusqu'à Juin 2027 Wed, 01 Jan 2025 00:00:00 GMT http://repository.enp.edu.dz/jspui/handle/123456789/11361 2025-01-01T00:00:00Z http://repository.enp.edu.dz/jspui/handle/123456789/11230 Fractional-Order Control of a Helicopter Flight Simulator (TRMS): Simulation and Experimentation Zerrougui, Yahya Moundher; Debache, Mounsef This project focuses on designing and optimizing fractional-order controllers for the Twin Rotor MIMO System (TRMS), a nonlinear and strongly coupled platform. Two strategies—FOPID and FOSMC—are developed and tuned using Particle Swarm Optimization (PSO). Simulation results show that fractional-order controllers offer superior performance over classical methods in terms of robustness, disturbance rejection, and handling system nonlinearities. Mémoire de Projet de Fin d’Études :Automatique: Alger, École Nationale Polytechnique :2025 Wed, 01 Jan 2025 00:00:00 GMT http://repository.enp.edu.dz/jspui/handle/123456789/11230 2025-01-01T00:00:00Z http://repository.enp.edu.dz/jspui/handle/123456789/11219 Modeling, Identification and Control Strategies for a Reverse Osmosis-Based Desalination System Guendouz, Khaled; Benseddik, Akram This thesis focuses on the modeling, identification, and control of a reverse osmosis (RO) desalination system. In response to the growing scarcity of freshwater resources, RO technology offers a viable and sustainable solution. The first phase involves the development of a dynamic model based on experimental data, accurately capturing the interactions between key variables such as feed pressure, pH, permeate flow rate, and conductivity. Two control strategies are explored : Model Predictive Control (MPC), implemented on both decoupled and multivariable models, and classical PID control, including an improved IMC-PID version. The results obtained highlight the performance, robustness, and limitations of each control approach under model uncertainties Mémoire de Projet de Fin d’Études:Automatique: Alger, École Nationale Polytechnique : 2025 Wed, 01 Jan 2025 00:00:00 GMT http://repository.enp.edu.dz/jspui/handle/123456789/11219 2025-01-01T00:00:00Z