This paper discusses the design and software-in-the-loop implementation of adaptive formation controllers for fixed-wing unmanned aerial vehicles (UAVs) with parametric uncertainty in their structure, namely uncertain mass and inertia. In... more
This paper discusses the design and software-in-the-loop implementation of adaptive formation controllers for fixed-wing unmanned aerial vehicles (UAVs) with parametric uncertainty in their structure, namely uncertain mass and inertia. In fact, when aiming at autonomous flight, such parameters cannot assumed to be known as they might vary during the mission (e.g. depending on the payload). Modeling and autopilot design for such autonomous fixed-wing UAVs are presented. The modeling is implemented in Matlab, while the autopilot is based on ArduPilot, a popular open-source autopilot suite. Specifically, the ArduPilot functionalities are emulated in Matlab according to the Ardupilot documentation and code, which allows us to perform software-in-the-loop simulations of teams of UAVs embedded with actual autopilot protocols. An overview of realtime path planning, trajectory tracking and formation control resulting from the proposed platform is given. The software-inthe-loop simulations show the capability of achieving different UAV formations while handling uncertain mass and inertia.
In current literature, Unmanned Aerial Vehicles (UAVs), especially quadrotors, is one of the hot topics of study which has numerous applications. This paper focuses on modeling the quadrotor in order to improve the empirical results. The... more
In current literature, Unmanned Aerial Vehicles (UAVs), especially quadrotors, is one of the hot topics of study which has numerous applications. This paper focuses on modeling the quadrotor in order to improve the empirical results. The procedure consists of four stages: 1) Experimental determination of controller coefficients, 2) Data collection, 3) System identification, 4) Controller redesign. After these stages, it is observed that the system is capable of stabilize on the roll, pitch and yaw axes. Coefficient tuning on the identified model noticeably improves the settling time and steady state oscillation amplitude.
An Unmanned Air Vehicle (UAV) or an autonomous quad copter has been developed for the purpose of agricultural surveillance. The quad copter is potentially designed for live monitoring of the entire agricultural field without the presence... more
An Unmanned Air Vehicle (UAV) or an autonomous quad copter has been developed for the purpose of agricultural surveillance. The quad copter is potentially designed for live monitoring of the entire agricultural field without the presence of the farmer in the farm. In other words the quad copter designed in autonomous mode inspects the farm field and provides live feedback to the farmer (base station) through wireless communication. The quad in the air can be controlled from the ground station through software called Mission Planner. In this paper the quad copter is designed to withstand the major challenges of flight i.e. wind, rain etc. The control system and stabilization of the quad is designed using PID algorithm. PID algorithm is a closed loop algorithm. The autonomous flight of the quad is implemented using Ardupilot APM 2.6, which is a low cost autopilot. The features like low cost and autonomous flight mode of quad copter makes it a multi-purpose vehicle and can be advantageous to commercial applications. In this experiment the quad copter is loaded with the source and destination way points, the quad copter follows the navigation points at defined height and speed in the autonomous mode and it can be transformed from autonomous flight mode to radio controlled vehicle simultaneously.
