In this paper, a hexarotor Unmanned Aerial Vehicle (UAV) flight dynamics is derived and its control system is designed. A complete mathematical model of the UAV is obtained using Newton–Euler formulation and it is used for simulation. However, a reduced model is derived for the control design purpose which is based on the backstepping approach for hexarotor attitude stabilization and altitude trajectory tracking. The main contribution of this paper consists of the introduction of a new compact Gravitational Search Algorithm (cGSA) and its application for improving the backstepping controller performances in terms of tracking errors. Indeed, using the compact optimization paradigm enhances the performances of classical Population-based Algorithms (PBAs). Moreover, the introduced cGSA is applied to compute the optimal gains of the considered controller. In addition, the cGSA is compared with two compact optimization algorithms that are compact Particle Swarm Optimization (cPSO) and compact Teaching Learning-Based Optimization (cTLBO). The proposed algorithm shows encouraging results.

Novel modeling of the raindrops impact forces on a quadrotor has been developed and implemented in this work. These forces are meant to generate dispersed displacement disturbances in the vertical axis Z_E and dispersed rotation disturbances around roll and pitch axis. The proposed model is derived using the stochastic characteristics of the raindrops combined with classical quadrotor dynamics to address the issue of the adopted sliding mode controller, which shows lack of robustness while tracking the desired path, resulting in sensitive fluctuations. These fluctuations are increasingly visible for disturbances generated by raindrops with an average diameter greater than 2 mm. To deal with these types of disturbances, a novel control law based on an adaptive sliding mode approach and the estimated parameters of the stochastic disturbances (average and variance) was employed. This control law has been synthesized based on the sliding mode approach and Lyapunov principle to ensure quadrotor stability and robustness purposes. The adopted estimation of the average and variance of the disturbances was carried out by filtering the difference between the system state and a reference model state. The adopted control law has been implemented on MATLAB/SIMULINK, yielding satisfactory results and minimizing the fluctuations.