Browsing by Author "Boushaki, Razika (supervisor)"

Now showing 1 - 13 of 13

Adaptive control for disturbance rejection in quadrotors.
(2021) Recham, Zine Eddine; Amrouche, Hafid; Boushaki, Razika (supervisor);
In order to fix the issue of precise trajectory tracking control for a quadrotor in the influence of environmental disturbance and system model parameter uncertainty, three control techniques were developed to control the quadrotor’s altitude, heading and position in space; the Proportional-Integral-Derivative or PID controller, the sliding mode controller and the backstepping controller. Simulation based experiments have been performed using MATLAB/SIMULINK to evaluate and compare between the three developed techniques in terms of dynamic performances, stability and disturbance effects.
Altitude backstepping control of quadcopter
(Université M’Hamed BOUGARA de Boumerdes : Institut de génie electrique et electronique (IGEE), 2018) Younes, Hamza; Boushaki, Razika (supervisor)
This work deals with the study of the stabilization process of a nonlinear control system taking a certain model and derive state space equations through implementation of kinetic and dynamic equations where we present a challenging tool known as backstepping controllers based on Energy functions concept as presented by the famous Russian mathematician Lyaponuv. Simulation of the obtained results is done with Simulink.
Control algorithms for autonomous quadrotors
(2021) Zerroug, Khalil; Larit, Mohamed Islem; Boushaki, Razika (supervisor)
In this thesis, a detailed mathematical model for a Vertical Take-off and Landing (VTOL) type Unmanned Aerial Vehicle (UAV) known as the quadrotor is presented. The nonlinear dynamic model has been derived using Newton's and Euler's laws. Three control approaches were developed to control the altitude, attitude, heading and position of the quadrotor in space. The first approach is based on a linear Proportional-Integral-Derivative (PID) controller. The second developed controller is Backstepping while the third one is a Gain Scheduling control. The Genetic Algorithm technique has been used to get an optimal tuning for the fore mentioned controllers (gains and parameters) and, hence, improving the dynamic response. Simulation based experiments were conducted using MATLAB to evaluate and compare between the three developed control techniques in terms of dynamic performance, stability and possible disturbances effect.
Control design and visual autonomous navigation of quadrotor
(2018) Boughellaba, Mouaad; Rabah hazila, Ramzi; Boushaki, Razika (supervisor)
Starting from the fact that quadrotors are nonlinear MIMO system that operates in 3D space, the task of stabilizing and generating suitable control commands have been the interest of many researches. Another challenging task is the autonomous navigation as both the weight and the computation capacity are limited which constrains the type of sensors and algorithms. In this project, an autonomous navigation and obstacle avoidance system based on monocular camera has been implemented which enables the quadrotor navigates in previously unknown GPS-denied environment. Moreover, four controllers have been designed and their performance were compared.The mathematical model of a
Design of a digital PI controller for a power factor correction boost converter
(2019) Bensidi Aissa, Elyes; Moudoud, Adel; Boushaki, Razika (supervisor)
The Power Factor Correction (PFC) is an important stage for the boost converter. Its controller is among the most complex with its two-loop structure and multiplier/divider. This project studies the design method of both analog and digital control for a PFC boost converter using Continuous Conduction Mode (CCM). The effectiveness of the solution is verified by simulation.
Fuzzy-PID speed controller for an induction motor
(2020) Bougheloum, Dhya Eddine; Benyahia, Sofiane; Boushaki, Razika (supervisor)
The main objective of vector control or field-oriented control (FOC) control is to have decoupled control of flux and torque in three phase induction motors. FOC rotates the stationary stator reference frame into rotating reference frame attached to the rotor flux linkage space phasor which results in a decomposition of stator currents into torque and flux producing components under orthogonality. This will give fast dynamic response as compares to other scalar drives i.e. variable frequency drive (V/F). This project presents a Fuzzy-PID control system for the speed control of a three-phase squirrel cage induction motor. The proposed method uses both Fuzzy logic and conventional controllers along with vector control technique. This method combines the advantages of the fuzzy logic controller and conventional controllers to improve the speed response of the induction motor. The FLC observes the closed loop error signal and then controls the PID input error signal so that the actual speed matches the reference speed with reduced rise time, settling time, and peak over shoot. Implementation and simulation results using MATLAB of multiple controllers such as (PID, Fuzzy, and Fuzzy-PID) are compared along with conventional PI controller in terms of some performance measurements such as rise time (tr), maximum percent overshoot (Mp), settling time (ts), and steady state error (Ess) at various load conditions. The results of the simulation verified the effectiveness of the proposed speed controller model under different operating conditions and demonstrated improvements in performance in speed tracking and system's stability.
Modeling and control of a quadrotor
(2019) Baiteche, Amin; Kennane, Oussama; Boushaki, Razika (supervisor)
The report presents the state-of-the-art methodologies used to control Quadrotor UAVs. Prior to the discussion of the control methodologies, a detailed description of the dynamic modelling of the Quadrotor is presented. Various control strategies like the Proportional Derivative Control, the Sliding Mode Control and the Backstepping Control methods have been elucidated and implemented in MATLAB and SIMULINK. Simulations have been carried out and the results have been presented.
Modeling and control of autonomous quadrotor
(2020) Belatreche, Ramzi; Boushaki, Razika (supervisor)
This project discusses the development of detailed mathematical model for specific type of an unmanned aerial vehicle (UAV), which has Vertical Takeoff and Landing (VTOL) ability, known as quadcopter. Mathematical model of quadrotor in state space form is derived; it utilizes Newton and Euler equations for three-dimensional motions. This mathematical model is nonlinear and accurate enough including the aerodynamic effects and rotor dynamics. Quadrotor dynamics can be divided into two subsystems; translational subsystem and rotational subsystem. Translational subsystem is an under actuated system as it depends on roll, pitch, yaw angles and the translational state variables. The rotational subsystem is fully-actuated and only depends on the rotational states. Then development of a nonlinear control approache to control the attitude and position of the quadrotor in space is discussed. A Sliding Mode Controller is designed to control the roll angle, pitch angle, yaw angle, altitude and positions. Simulation results after implementation SMC controller on MATLAB/Simulink are presented.
Modeling and control of autonomous quadrotor
(2020) Hamdous, Gaya; Bahmed, Kousseila; Boushaki, Razika (supervisor)
In this work, a detailed mathematical model for a quadrotor UAV is presented. The non- linear model has been derived using both Newton’s and Euler’s laws and then linearized around an equilibrium point. Three linear control techniques were developed to control the quadrotor’s altitude, attitude, heading and position in space; a linear Proportional-Integral- Derivative, or PID, controller, a linear Proportional-Derivative, PD, Controller and a PD based Gain Scheduling Controller. Ziegler-Nichols for tuning PID has been used to tune the PID and PD parameters and Genetic Algorithm has been used to tune the PD based Gain Scheduling controller. Simulation based experiments have been conducted using MATLAB/SIMULINK to evaluate and compare between the three developed approaches in term of dynamic performances, stability and disturbance effects.
Modeling and control of mini unmanned aerial vehicles (UAV)
(2019) Dorbane, Sedik; Ait Said, Azouaou; Boushaki, Razika (supervisor)
In this work, a detailed mathematical model for a Vertical Takeoff and Landing type Unmanned Aerial Vehicle known as the quadrotor is presented. The nonlinear dynamic model has been derived using Newton's and Euler's laws. Three control approaches were developed to control the altitude, attitude, heading and position of the quadrotor in space. The first approach is based on a linear Proportional-Integral-Derivative (PID) controller. The second developed controller is a nonlinear Back-stepping controller while the third one is a gain Grain-Scheduling based PID controller. The Genetic Algorithm technique has been used to get an optimal tuning for the fore mentioned controllers (gains and parameters) and, hence, improving the dynamic response. Simulation based experiments were conducted using MATLAB to evaluate and compare between the three developed control techniques in terms of dynamic performance, stability and possible disturbances effect.
Simulation of robust controllers for disturbance rejection in ouad-copter
(2021) Belkheir, Rabia; Boushaki, Razika (supervisor)
In this work kinematics and dynamics of a quad-copter were presented, the quad-copter is studied in two frames: inertial or earth frame and body frame, the first is attached to the ground and the latter is attached to the aircraft's center. Forces and moments acting on the drone were studied as well as aerodynamic effects and rotor dynamics. From this information, a state space model was derived which was used to design three controllers to stabilize the system. When building the model the quad-copter and propellers are assumed to be rigid. One controller was a PID and the others followed Backstepping and Gain-scheduling methods. PID is a linear controller that minimizes the error between actual and desired states through proportional; integral and derivative terms. Backstepping is a method developed for nonlinear systems that can be decomposed into smaller subsystems and then controlling inputs are derived based on Lyapunov theory of stability. As for Gain-scheduling, it is an expansion of the PID method to be suitable for nonlinear systems where multiple PID controllers are used, switching between controllers is based on a scheduling variable, in this thesis the scheduling variable was chosen to be the desired state. In all these controllers parameters are tuned using repetitive trials until satisfactory outcome is achieved. In the end, simulation results were presented and discussed. Additionally, advantages and disadvantage of each method are highlighted to conclude with a comparison between the three controllers.
Speed control of induction motor using three fuzzy logic-based controllers
(2021) Yahia, Amina; Bouyahia, Hadjer; Boushaki, Razika (supervisor)
This work portrays the methods for controlling an induction motor using three different types of fuzzy controllers: single-stage fuzzy controller; fuzzy-PID controller and adaptive- fuzzy-PID controller. The comparative performance of these three techniques has been presented and analyzed in this work. The proposed scheme uses indirect field oriented control and is simulated using MATLAB. The IFOC accepts two inputs: the reference torque from the speed controller and the measured current feedback. Using the Clark and Park transformations, the current is transformed from the three phase to the rotating reference frame. The new reference currents are then measured before being transformed back to the three phase using inverse Park and Clark. The new reference current will be fed to the hysteresis current controller for current tracking then to the three-phase inverter. Finally, the inverter is connected to the squirrel cage induction motor. The first speed controller consists of a simple single-stage fuzzy controller. This fuzzy controller regulates the output torque depending on the error and error ratio ranges, which are chosen according to the if-then rules. The second controller demonstrates the speed control using a fuzzy-PID control. A PID controller is connected to the fuzzy controller. The gain parameters of the PID are fixed. The third controller displays the Adaptive-fuzzy PID controller. It is also called multiple-stage controller since three fuzzy blocks are used. Each controller is used to adjust the gain values of the PID, depending on the changes in the error and error ration. The ranges of the membership functions are determined using error-and-trial method. Then the PID uses these gain values, alongside the error value to calculate the torque value.
Trajectory tracking based on sliding mode control for a quadrotor
(2019) Bouanzoul, Mahdi; Aouati, Ayoub; Boushaki, Razika (supervisor)
In order to solve the problem of precise trajectory tracking control for a quadrotor in the presence of external disturbance and system model parameter uncertainty, a nonlinear trajectory tracking controller based on sliding mode for the quadrotor is designed. The dynamic model is used to design a stable and accurate controller to perform the best tracking and attitude results. The robustness and effectiveness of the proposed control strategy is verified by simulation in a virtual environment for linear and nonlinear trajectories.