Browsing by Author "Boushaki, Razika"

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Backstepping Control of Drone †
(MDPI, 2022) Saibi, Ali; Boushaki, Razika; Belaidi, Hadjira
This work derives the models which can be used to design and implement control laws for six degrees-of-freedom (DOF) quadrotor stability. The first part of this paper deals with the presentation of the background of quadrotor modeling; the second part describes the direct control of the drone using the backstepping control principal. This principal is based on the division of the system into several sub-systems in a cascade, which makes the control laws generated on each subsystem, in a decreasing manner, until a global control law for the whole system is generated. The simulation results for the sm controller are generated on the MATLAB/Simulink platform; the results show a good performance in both the transient and steady-state operations.
Enhanced backstepping control for disturbances rejection in quadrotors
(2022) Saibi, Ali; Belaidi, Hadjira; Boushaki, Razika; Recham, Zine Eddine; Amrouche, Hafid
This work studies the issue of quadrotor trajectory tracking control in presence of disturbances and model uncertainties. The paper starts by extracting the kinematics and dynamics models of the quadrotor. This results in the motion equations, which eventually serve as a blueprint for creating the suggested smart flight control scheme. Secondly, an enhanced backstepping controller (BSC) is developed and tested to keep the quadrotor tracking the desired trajectory both in steady state and in presence of disturbances. Finally, BSC beside two other controllers: sliding mode controller (SMC) and proportional derivative controller (PDC) are implemented in MATLAB/Simulink and the obtained results are compared and conclusions are extracted. Therefore, it is established that PDC is not robust to disturbances as noise will be amplified due to the derivative term. Whereas, although SMC is robust to parameter variations and disturbances; however, it is not continuous which may affect the actuators due to the increased gains which may saturate them. In contrast, BSC requires too many tuning parameters; however, it ensures Lyapunov Stability and does not depend on the system as it does not involve cancelling system nonlinearity. Moreover, BSC results are 1017 better than the results of the two other controllers.
Enhancing quadcopter autonomy: implementing advanced control strategies and intelligent trajectory planning
(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Hadid, Samira; Boushaki, Razika; Boumchedda, Fatiha; Merad, Sabrina
In this work, an in-depth investigation into enhancing quadcopter autonomy and control capabilities is presented. The focus lies on the development and implementation of three conventional control strategies to regulate the behavior of quadcopter UAVs: a proportional–integral–derivative (PID) controller, a sliding mode controller, and a fractional-order PID (FOPID) controller. Utilizing careful adjustments and fine-tuning, each control strategy is customized to attain the desired dynamic response and stability during quadcopter flight. Additionally, an approach called Dyna-Q learning for obstacle avoidance is introduced and seamlessly integrated into the control system. Leveraging MATLAB as a powerful tool, the quadcopter is empowered to autonomously navigate complex environments, adeptly avoiding obstacles through real-time learning and decision-making processes. Extensive simulation experiments and evaluations, conducted in MATLAB 2018a, precisely compare the performance of the different control strategies, including the Dyna-Q learning-based obstacle avoidance technique. This comprehensive analysis allows us to understand the strengths and limitations of each approach, guiding the selection of the most effective control strategy for specific application scenarios. Overall, this research presents valuable insights and solutions for optimizing flight stability and enabling secure and efficient operations in diverse real-world scenarios.
Nonlinear Control Algorithms Applications for Quadrotor
(Institute of Electrical and Electronics Engineers Inc, 2023) Bourouis, Imane Belquis; Boushaki, Razika; Larit, Islem Mohamed; Zerroug, Khalil; Aribi, Yacine; Kouzou, Abdellah
In this article, we present a detailed mathematical model for a vertical take-off and landing (VTOL) type unmanned aerial vehicle (UAV) known as a quadrotor. 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.
State feedback linearization using block companion similarity transformation
(Institute of Advanced Engineering and Science, 2021) Kessal, Farida; Hariche, Kamel; Bentarzi, Hamid; Boushaki, Razika
In this research work, a new method is proposed for linearizing a class of nonlinear multivariable system; where the number of inputs divides exactly the number of states. The idea of proposed method consists in representing the original nonlinear system into a state-dependent coefficient form and applying block similarity transformations that allow getting the linearized system in block companion form. Because the linearized system’s eigenstructure can determine system performance and robustness far more directly and explicitly than other indicators, the given class multivariable system is chosen. Examples are used to illustrate the application and show the effectiveness of the given approach