In this paper, the conceptual design, modeling, and simulation are proposed for an octorotor UAV with a manipulator arm. The conceptual design of the octorotor UAV with a manipulator arm is developed, and for the study and analysis, the design is implemented and validated in Matlab (Simulink-SimMechanics) software. The kinematics and dynamics models of the octorotor UAV with a manipulator arm are obtained using the classical Denavit–Hartenberg convention and the recursive Newton–Euler method, respectively. In this sense, a cascade PID controller for the attitude and navigation of the UAV and a simple PID controller for the manipulator arm are proposed and simulated in a closed-loop system in order to highlight the performance of the proposed design. Finally, simulations show the feasibility and behavior of the mathematical model and the flight controller in a closed-loop system.

In this research, a proportional plus integral plus velocity (PIV) fuzzy gain scheduling flight controller for an octorotor mini-unmanned aerial vehicle is developed. The designed flight controller scheme, with a PIV term, is combined with a fuzzy gain scheduling approach. The tracking controller PIV fuzzy gain scheduling is based on two controllers connected in cascade with a saturation approach. The Newton–Euler equations of motion are applied to obtain a mathematical model for the octorotor mini-unmanned aerial vehicle (mini-UAV). The flight controller approach is applied to obtain coupling moments and forces with interconnected attitude and navigation tracking trajectory. In the design of a flight navigation controller with two layers, the inner layer consists of a PIV fuzzy gain scheduling controller that is applied to the attitude dynamics, obtaining the references for the coupling outer layer PIV fuzzy gain scheduling controller, which manipulates the translational dynamics. The navigation PIV fuzzy gain scheduling controller is saturated for bounding in translational forces to avoid large deviations of commands to Euler angles pitch and roll, and another saturated controller is implemented for the bounded thrust rotor to avoid the excessive angular speed of these rotors. The octorotor mini-UAV flight navigation simulation is performed to validate the tracking control of a sequence of motions in each axis, which is presented as a validation for the proposed control scheme.

The translational and rotational dynamics of quadrotor UAVs are commonly described by mathematical modeling where aerodynamic and inertial parameters are involved. Therefore, the importance of having accurate parameters in the model is critical for the correct performance of the UAV. In this paper, Artificial Neural Networks (ANNs) are used to estimate the aerodynamic and inertial parameters corresponding to the mathematical model of a quadrotor. Thrust and torque coefficients from the rotor models and the quadrotor inertia matrix are estimated by proposing and training two different ANN models implementing the back-propagation algorithm, using both experimental and simulation data. The estimated parameters are then compared with the reference parameters by means of quadrotor attitude simulations, showing high accuracy in their behavior. The results have shown that the proposed ANN models can accurately estimate both the aerodynamic and inertial parameters of a quadrotor UAV model using both experimental and simulation data, thus contributing to increasing the tools available for parameter estimation.

This study presents the nonlinear aerodynamic modeling of a convertible uncrewed aerial vehicle (CUAV) designed for operation in constrained environments, integrating the advantages of fixed-wing and rotary-wing flight. The CUAV is capable of vertical takeoff and landing (VTOL) and smoothly transitions to horizontal flight after reaching a target altitude. The vehicle features a propulsion system, vertical stabilizer, and tapered wing configuration to mitigate the effects of the wingtip vortex and improve aerodynamic efficiency. The transitional flight behavior is analyzed across a range of angles of attack to represent different flight regimes. The nonlinear model incorporates Reynolds-averaged Navier–Stokes (RANS) equations, evaluating both one-equation and two-equation turbulence models to assess turbulent viscosity effects. Simulations using computational fluid dynamics (CFD) are performed to assess the CUAV configuration, with particular emphasis on the impact of turbulence modeling on aerodynamic performance. The results confirm the vehicle capability to operate efficiently across the full flight envelope.

In this research work, the design of a PID flight controller with the rules of an expert system was applied to the navigation of an octocopter UAV. The Newton-Euler mathematical formulation is used to calculate the dynamic model of the octocopter UAV. The proposed set of decision rules for the Expert PID flight controller design allows the moment controllers to increase their response capability versus error variations. The simulation results of the navigation algorithm implemented in the octocopter UAV demonstrate that the translation Expert PID controller in interconnection with the attitude Expert PID controller can track a helical trajectory, fulfilling the objective of

En los últimos años, la impresión 3D se ha popularizado para crear componentes estructurales de polímero, como los frames de los cuadrirrotores. Por otro lado, el modelado matemático de vehículos aéreos no tripulados mediante algoritmos inteligentes también ha sido objeto de estudio. Sin embargo, se han realizado pocas contribuciones con datos experimentales para validar la estructura, el modelo matemático y los parámetros de un cuadrirrotor impreso en 3D. Por lo tanto, el objetivo de este trabajo es presentar una metodología para validar experimentalmente la estructura del frame de un cuadrirrotor impreso en 3D, su modelo matemático y sus parámetros mediante redes neuronales. Los resultados muestran un desempeño adecuado del cuadrirrotor en condiciones de vuelo.