ABSTRACT Multirotor Aerial Vehicles may be fault-tolerant by design when rotor-failure is possible to measure or identify, especially when a large number of rotors are used. For instance, an octocopter can be capable to complete some missions even when a double-rotor fault occurs during the execution. In this paper, we study how a rotor-failure reduces the vehicle control admissible set and its importance with respect to the selected mission, i.e. we perform mission-related fault-tolerant analysis. Furthermore, we propose a risk-sensitive motion-planning algorithm capable to take into account the risks during the planning stage by means of mission-related fault-tolerant analysis. We show that the proposed approach is much less conservative in terms of selected performance measures than a conservative risk planner that assumes that the considered fault will certainly occur during the mission execution. As expected, the proposed risk-sensitive motion planner is also readier for accepting failures during the mission execution than the risk-insensitive approach that assumes no failure will occur.

This paper presents a numerical analysis of a reinforced concrete beam in which the concrete and reinforcement are above the yield strength of the material. Further, the procedure for determining the relationship between the cross-sectional forces and the deformations of the layered cross-section of a rod is described. For a short rod with reduced stiffness of the EI and EA cross-sections, a stiffness matrix with variable members is formed. The applicability of the proposed analysis method for the material nonlinearity in a beam calculation is demonstrated through a numerical example. The aim of the present paper is to show the flow of plastification and the load deformation of the system nodes. Finally, the results of the manual deformation calculation system are compared with the results from SCIA software.

In this paper Failure Mode and Effects Analysis (FMEA) for a large scale multirotor systems (with moving mass) based on novel system for aircraft control will be presented. This system uses four petrol engines for lift and a moving mass system to control the vehicle. Analysis presented in this paper assesses the vulnerabilities of the system during the vehicle operation. The main objective of the analysis is to understand the cause and severity of the failures that can occur to the petrol engines and the moving mass system. Our unmanned aerial vehicle system is used for environmental monitoring and maritime security developed under MORUS project funded under NATO SPS Program. The ultimate goal of our research and design is to make an unmanned aerial vehicle that can lift larger amount of load (approximately 40kg). During its operation time the unmanned aerial vehicle might fail to complete a certain assignment so failure mode and effects analysis is needed to account for such problems and to find appropriate activities to reduce the overall risk the system faces during the mission.

This paper presents an experimental procedure for the identification of parameters of an octorotor unmanned aerial vehicle (UAV), as well as the obtained model validation via control. The octorotor UAV is a highly nonlinear, multivariable and strongly coupled system. The mathematical model of used UAV includes rigid body dynamics, the Gyroscopic effect and motor dynamics. In order to estimate eleven unknown parameters, the experiments are specially prepared and conducted on the custom made apparatus. Therefore, on basis of obtained measurements, some modifications of the octorotor model are made.

This paper presents a generalized Multirotor Aerial Vehicle (MAV) modeling framework which includes rigid body dynamics, gyroscopic effect and motor dynamics. We illustrate how this model can be used to derive any MAV platform constructed with an arbitrary number of rotors by using the quadrotor case as an example. Based on this result, we design the first Modelica-based MAV simulator. We validate the proposed design by using a simple altitude and attitude stabilization control system through a Modelica simulation setup.