Quadcopter unmanned aerial vehicles (UAVs) systems are receiving remarkable attention from researchers due to their daily use in numerous applications, particularly at the current time where UAVs are playing a significant role in combating the COVID-19 pandemic. This paper is concerned with the problem of UAV navigation and control in the presence of uncertainty and external disturbances. It addresses this issue by proposing an improved adaptive sliding mode control (IASMC). Improved control law generates an adaptive switching gain achieving fast adaptation and robustness against both parameter uncertainties and external disturbances. Simultaneously, the control law allows for maintaining robust trajectory tracking with chattering attenuation. The performance of the proposed IASMC controller has been evaluated using a Matlab/Simulink platform. The obtained simulation results showed that the proposed IASMC control scheme as an inner loop controller is robust when dealing with uncertainties and can effectively track the desired trajectories while significantly attenuating the well-known chattering introduced by the SMC controller.

The quadcopter unmanned aerial vehicle (UAV) system is considered a good platform for control scheme design as it is highly nonlinear with coupled dynamics and an under-actuated system. Considering these challenges, this manuscript aimed to propose a control algorithm to control the quadcopter system in the presence of uncertainty and disturbance influences. The integral adaptive sliding mode control scheme has been proposed to control the system. The proposed control scheme is composed of the outer loop controller to control the position of the quadcopter, while the inner loop controls the attitude of the quadcopter. The proposed control law has three major terms, firstly the equivalent control which is developed based on the Lyapunov approach to handle most of the uncertainty and disturbance, secondly the adaptive switching gain, which is achieving fast adaptation against uncertainty, finally the switching function which has been approximated by a tangent hyperbolic function to reduce the unwanted chattering phenomena. The proposed control scheme and its performance have been investigated via a MATLAB/Simulink. The results prove that the implemented control scheme is robust even in the presence of uncertainties and disturbance and the quadcopter tracks the predefined trajectories with limited chattering influence.

This paper presents a comparative analysis of a fractional-order proportional–integral–derivative (FO-PID) controller against the standard proportional–integral–derivative (PID) controller, applied to a nonlinear robotic arm manipulator systems. The genetic algorithm (GA) optimization method was implemented to tune the gain parameters of the FO-PID and PID controllers. The performance of the FO-PID and PID controllers were evaluated though different cost functions, including integral of squared error (ISE), integral of absolute error (IAE), integral of time-weighted absolute error (ITAE), and integral of time-weighted squared error (ITSE). The performance of these controllers was examined via extensive simulations by using MATLAB/SIMULINK for different operating scenarios of the robotic arm manipulator system. Based on the obtained results, a comparative performance matrix is proposed, wherein cost functions ISE, IAE, ITAE, and ITSE are represented as columns while characteristic parameters (overshoot, rising time, and settling time) are represented as rows. The proposed performance matrix facilitates the selection between the PID and FO-PID controllers.

The paper introduces a robust adaptive fault-tolerant control system for the six-degree-of-freedom (six-DOF) dynamics of quadrotor unmanned aerial vehicles (UAVs), incorporating disturbances and abrupt actuator faults to represent real-world conditions. The proposed control scheme employs robust control terms to manage unknown disturbances. However, robust control performance may degrade due to sudden fault impacts. To handle this issue, we introduce adaptive laws to ensure continuous adaptation. The control architecture ensures the tracking system’s stability by combining robust control using sliding-mode control (SMC) with adaptive control developed using the certainty equivalence principle. The sliding-surface error limits the adaptive laws, in which the convergence of estimated parameters to the actual unknown variables is not required as they fully rely on the convergence of the tracking error. We provide rigorous mathematics to validate the proposed control design. Furthermore, we conduct numerical simulations for a quadrotor UAV to showcase the effectiveness of the proposed scheme. The results demonstrate the efficacy of the proposed design in handling external disturbances and abrupt actuator faults.

This work is focused on the kinematic analyses and simulation of the Delta parallel robot. Thisrobot is proposed in this study, which solves the forward kinematics by vector method. The half-angle formulais used to derive the inverse kinematics. The workspace of the Delta robot is presented dependent on thesolution of forward kinematics. This parallel robot model was built in Solidworks and then imported intoMATLAB/Simscape to do the simulation. The simulation represents the position and velocity of the movingplate, study the angular position and velocity of each joint.