This paper shows a proposal for a control scheme for the trajectory tracking problem in a Two Degree of Freedom Helicopter (2DOFH). For this purpose, a control scheme based on a feedback linearization combined with a Generalized Proportional Integral (GPI) controller is used. In order to implement linearization by feedback, it is required to know and have access to all the physical 2DOFH parameters, however, angular velocity and viscous friction are often not available. Commonly, state observers are used to know the angular velocity, however, estimating friction results out to be more complex. Therefore, we propose the use of a Convolutional Neural Network (CNN) to estimate viscous friction and angular velocity. The variables estimated by the CNN are entered into both the GPI and feedforward controllers. Thus, the system is brought to a linear representation that directly relates the GPI control to the dynamics of perturbations and non-model parameters. Finally, results of numerical simulations are shown that validate the robustness of our scheme in the presence of disturbances in the tail rotor, as well as the advantages of using a feedforward control based on a CNN.

The use of sensor networks in monitoring applications has increased; they are useful in security, environmental, and health applications, among others. These networks usually transmit data through short-range stations, which makes them attractive for incorporation into applications and devices for use in places without access to satellite or mobile signals, for example, forests, seas, and jungles. To this end, unmanned aerial vehicles (UAVs) have attractive characteristics for data collection and transmission in remote areas without infrastructure. Integrating systems based on wireless sensors and UAVs seems to be an economical and easy-to-use solution. However, the main difficulty is the amount of data sent, which affects the communication time and even the flight status of the UAV. Additionally, factors such as the UAV model and the hardware used for these tasks must be considered. Based on those difficulties mentioned, this paper proposes a system based on long-range (LoRa) technology. We present a low-cost wireless sensor network that is flexible, easy to deploy, and capable of collecting/sending data via LoRa transceivers. The readings obtained are packaged and sent to a UAV. The UAV performs predefined flights at a constant height of 30 m and with a direct line-of-sight (LoS) to the stations, during which it collects information from two data stations, concluding that it is possible to carry out a correct data transmission with a flight speed of 10 m/s and a transmission radius of 690 m for a group of three packages confirmed by 20 messages each. Thus, it is possible to collect data from routes of up to 8 km for each battery charge, considering the return of the UAV.

This article deals with modelling and a flatness-based robust trajectory tracking scheme for a two degrees of freedom helicopter, which is subject to four...

La dinámica altamente no lineal y las propiedades de vuelo de los vehículos aéreos no tripulados (VANT) tipo quadrotor continúan despertando el interés de investigadores de diversas áreas. En particular, en el área de control automático se trabaja en el desarrollo de nuevos esquemas de control, de los cuales, muchos no llegan a la etapa de implementación. En ese sentido, el Hardware-In-the-Loop (HIL) resulta atractivo para el desarrollo y comprobación de sistemas de control. Por lo anterior, en este trabajo se muestra el uso MATLAB/Simulink y X-Plane como herramientas de co-simulación para analizar el comportamiento y control de un quadrotor. Se utiliza un control prealimentado tipo PID para realizar maniobras de vuelo en estado estacionario ante la presencia de diferentes velocidades de viento. Los datos de retroalimentación del esquema de control se obtienen de X-Plane a través de la comunicación basada en el Protocolo de Datagramas de Usuario (por sus siglas en inglés, UDP), estos son enviados a Simulink para su uso en el cálculo de las acciones de control, posteriormente, las acciones de control pasan por una matriz de transformación que convierte dichas acciones en velocidades angulares de los rotores (información enviada a X-Plane). Por último, se reportan los resultados del esquema control ante diferentes velocidades de viento, siendo 50 Nudos (kt) la máxima velocidad que puede compensar el controlador propuesto.

La aeronave de rotor basculante es un diseño híbrido que combina los modos de vuelo de ala fija y ala rotatoria, de esta forma, combina las ventajas de vuelo de los aviones y los helicópteros. En este artículo se presenta la descripción de las aeronaves híbridas en modo de vuelo y el estado del arte del desarrollo de modelos de aeronaves híbridas, y esquemas de control. Se exponen diferentes modelos mecánicos de aeronaves que incluyen mecanismos para la transición de modo de vuelo de ala rotatoria a ala fija y viceversa. También, se formula el modelo matemático empleado comúnmente en los trabajos reportados, así como el planteamiento de algoritmos de control propuestos enfocados en la estabilidad de las aeronaves en su transición de modo de vuelo.