Autopilot construction in the longitudinal and transverse sections of a plane using adaptive

Abstract

In this research, a simulation model of a non-linear model for unmanned neural vehicles is developed using Airsim (simulator via an open-source platform for drones and ground vehicles ). The non-linear model of the vehicle is approximated as a linear model with a balance point in the first stage. With this model, a conventional controller is designed to have longitudinal and transverse sections, and this controller is added to the non-linear model. Then, a neural network is  introduced to the traditional controller to perform the error compensation process after the approximation of the non-linear model with a linear model. The calculated results from the neural network that depended upon the  error process are added to the results that obtained from the non-Linear model and the linear model to the conventional microcontroller. Results show that the adaptive controller could achieve stability for the system for a wide range of aviation envelope. Thus, the use of an adaptive controller that consists  of  a traditional controller and a neurological compensator can compensate for  various disorders that may occur in vehicles, such as changes in altitude, direction and pressure disturbance .