Robust hovering control of a quad tilt-wing UAV

This paper presents design of a robust hovering controller for a quad tilt-wing UAV to hover at a desired position under external wind and aerodynamic disturbances. Wind and the aerodynamic disturbances are modeled using the Dryden model. In order to increase the robustness of the system, a disturbance observer is utilized to estimate the unknown disturbances acting on the system. Nonlinear terms which appear in the dynamics of the vehicle are also treated as disturbances and included in the total disturbance. Proper compensation of disturbances implies a linear model with nominal parameters. Thus, for robust hovering control, only PID type simple controllers have been employed and their performances have been found very satisfactory. Proposed hovering controller has been verified with several simulations and experiments

Development of c-means Clustering Based Adaptive Fuzzy Controller for A Flapping Wing Micro Air Vehicle

Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV) and its control is one of the recent research topics related to the field of autonomous Unmanned Aerial Vehicles (UAVs). In this work, a four wing Natureinspired (NI) FW MAV is modeled and controlled inspiring by its advanced features like quick flight, vertical take-off and landing, hovering, and fast turn, and enhanced manoeuvrability when contrasted with comparable-sized fixed and rotary wing UAVs. The Fuzzy C-Means (FCM) clustering algorithm is utilized to demonstrate the NIFW MAV model, which has points of interest over first principle based modelling since it does not depend on the system dynamics, rather based on data and can incorporate various uncertainties like sensor error. The same clustering strategy is used to develop an adaptive fuzzy controller. The controller is then utilized to control the altitude of the NIFW MAV, that can adapt with environmental disturbances by tuning the antecedent and consequent parameters of the fuzzy system.Comment: this paper is currently under review in Journal of Artificial Intelligence and Soft Computing Researc

The Phoenix Drone: An Open-Source Dual-Rotor Tail-Sitter Platform for Research and Education

In this paper, we introduce the Phoenix drone: the first completely open-source tail-sitter micro aerial vehicle (MAV) platform. The vehicle has a highly versatile, dual-rotor design and is engineered to be low-cost and easily extensible/modifiable. Our open-source release includes all of the design documents, software resources, and simulation tools needed to build and fly a high-performance tail-sitter for research and educational purposes. The drone has been developed for precision flight with a high degree of control authority. Our design methodology included extensive testing and characterization of the aerodynamic properties of the vehicle. The platform incorporates many off-the-shelf components and 3D-printed parts, in order to keep the cost down. Nonetheless, the paper includes results from flight trials which demonstrate that the vehicle is capable of very stable hovering and accurate trajectory tracking. Our hope is that the open-source Phoenix reference design will be useful to both researchers and educators. In particular, the details in this paper and the available open-source materials should enable learners to gain an understanding of aerodynamics, flight control, state estimation, software design, and simulation, while experimenting with a unique aerial robot.Comment: In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA'19), Montreal, Canada, May 20-24, 201