Mehdi Zareb

Bio: Mehdi Zareb is an academic researcher from University of Oran. The author has contributed to research in topics: Control theory & PID controller. The author has an hindex of 4, co-authored 10 publications receiving 65 citations. Previous affiliations of Mehdi Zareb include University of Science and Technology of Oran Mohamed-Boudiaf.

Energy Based 3D Autopilot for VTOL UAV Under Guidance & Navigation Constraints

Abstract: Motion control design plays a crucial role in autonomous vehicles. Mainly, these systems operate in conditions of under-actuation, which make the control a serious task especially in presence of practical constraints. The main objective within this paper is to ensure the tracking of 3D reference trajectory overcoming some of the issues related to the control of multi-rotor vehicles (such as underactuation, robustness, limited power, accuracy, overshoot, etc.). Therefore, a control scheme for Vertical Take Off and Landing (VTOL) multi-rotor Unmanned Aerial Vehicle (UAV) is designed, applying the Interconnection and Damping Assignment-Passivity Based Control (IDA-PBC) technique. As reference model based technique, the control specifications are readily met by fixing a desired dynamic model, which is a major advantage of the technique. Moreover, a port −controlled Hamiltonian representation is exploited in order to point out the physical properties of the system such as its internal energy. This latter is exploited, as a fitness function for an optimization algorithm, in order to decrease the consumed energy especially at the take-off step and allows the tuning of the controller parameters. The numerical simulations have shown satisfactory results that support the claims using nominal system model or disturbed model. The designed controller has been implemented on a real vehicle for which one demonstrates, in an indoor area manipulation, the effectiveness of the proposed control strategy.

Fuzzy-PID hybrid control system to navigate an autonomous mini-Quadrotor

Abstract: This paper report on the synthesis of a flight control system for an autonomous mini-Quadrotor. This system is developed on the base of realistic non-linear mathematical model. It's consisting of hybrid controllers, two controllers are Mamdani-type fuzzy controllers for attitude control. These fuzzy controllers are designed using a simple rule base. Four conventional SISO PID controllers are also used for roll, pitch, yaw angles and altitude control, Performance issues of flight control system are illustrated in a simulator of the Quadrotor in Matlab Simulink. The results show that the overall system becomes stable and robust.

Full Control of Quadrotor Aerial Robot Using Fractional-Order FOPID

Abstract: This article presents a new design of fractional order $$P I^\lambda \ D^\mu $$ , for the full control of quadrotor (attitude and position)using a modified Black–Nichols method. First, we use single-input–single-output approach to design fractional-order $$P I^\lambda \ D^\mu $$ controllers for each position and attitude component. After that, we employ the same $$P I^\lambda \ D^\mu $$ controllers in the multiple-input–multiple-output model of quadrotor to test their performance. It is shown that we can improve the robustness and performance of the control significantly. Fractional-order modeling and control toolbox is used with Simulink model of quadrotor to prove and validate the performance of our controllers considering several scenarios.

Evolutionary Autopilot Design Approach for UAV Quadrotor by Using GA

Abstract: This paper presents an off-line design strategy of an intelligent 3D autopilot of Micro-UAV Quadrotor. It consists of hybridization between two fuzzy controllers for the x and y motions and four PID classical controllers for the attitude/altitude motions. Genetic algorithms are used to adapt and optimize the value of the six controllers' parameters to achieve the best performance and decrease the consumed energy. Also, in order to ensure the global optimum control parameters, genetic algorithm named Bi-GA is used to automatically configure the two GAs using for the tuning process. This design strategy can be used to different types of Quadrotor (with cross or X configuration). Initially, in order to get the controller parameters, simulation tests are made on a commercial Quadrotor named AR.Drone V2. Finally, these parameters values are tested in an experiment using the robot operating system. The results of these experimentations confirm the effectiveness of using genetic algorithms in the design of intelligent PID autopilot.

Quadrotor Guidance-Control for flight like nonholonomic vehicles

Abstract: This paper introduces a velocity based guidance strategy for 3D time-prescribed path following. A second alternative, acceleration based guidance law that incorporates an integral action, is proposed to deal with the more adverse environments. The proposed strategy, which is combined with an efficient nonlinear control strategy for under-actuated systems, is applied to a quadrotor. It ensures the convergence toward the reference trajectory and allows the quadrotor to imitate the behavior of a fixed-wing UAV in the plane (non-holonomic like-navigation). The effectiveness of the proposed Guidance & Control (G&C) loop is shown through some numerical simulations.

L2 Gain And Passivity Techniques In Nonlinear Control

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Robust adaptive nonsingular fast terminal sliding-mode tracking control for an uncertain quadrotor UAV subjected to disturbances

Abstract: This paper investigates the design of a robust controller for the trajectory tracking problem of an under-actuated quadrotor UAV subject to the modeling uncertainties and unknown external disturbances. A new robust nonlinear adaptive controller is proposed for orientation and translation tracking by using the Adaptive Nonsingular Fast Terminal Sliding-Mode Control (ANFTSMC) algorithms. The ANFTSM control law: (i) ensures fast convergence, i.e. the quadrotor outputs achieve to the original values in a short finite-time; ( i i ) avoids singularities; ( i i i ) solves the chattering effect; ( i v ) offers robustness against the unknown external disturbances and uncertainties. Furthermore, the system unknown uncertainty and external disturbances upper bound are coped by the proposed control approach. Online estimation of these upper bounds is only introduced by velocity and position measurements. In addition, the control law applies the Lyapunov theory, guarantees the closed-loop stability of the quadrotor system. Finally, various simulations under different scenarios in terms of external disturbances and parametric uncertainties are carried out to evaluate/emphasize the effectiveness of the ANFTSMC strategy proposed in this work. Moreover, a comparative study is accomplished at the end of the present paper and shows clearly the outperformance of the proposed control scheme.

A Survey on Fractional Order Control Techniques for Unmanned Aerial and Ground Vehicles

Abstract: In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade.

Path Following Control of Quadrotor UAV With Continuous Fractional-Order Super Twisting Sliding Mode

Abstract: Quadrotors are highly maneuverable drones, which are susceptible to the parameter uncertainties such as the mass, drag coefficients, and moment of inertia. Whose nonlinearities, aerodynamic disturbances, and higher coupling between the rotational and the translational dynamics stand for a problem that demands a robust controller. In the present paper, a fractional order (FO) improved super twisting proportional-integral-derivative sliding-mode control (STPIDSMC) is proposed for the quadrotor system. To improve the speed tracking performance, a FOPIDSM surface is designed. Moreover, the proposed FO control approach ensures fast convergence, high precision, good robustness against stochastic perturbations and uncertainties. Finally, the performance of the FOSTPIDSMC is investigated under different scenarios. The simulation results clearly show the high control performance, efficiency and high disturbance rejection capacity of the controller strategy proposed in this work in comparison with the nonlinear internal model control (NLIMC) and FO backstepping sliding mode control (FOBSMC) strategies.