This article describes research on the classification of flight phases using a fuzzy inference system and an artificial neural network. The aim of the research was to identify a small set of input parameters that would ensure correct flight phase classification using a simple classifier, meaning a neural network with a low number of neurons and a fuzzy inference system with a small rule base. This was done to ensure that the created classifier could be implemented in control units with limited computational power in small affordable UAVs. The functionality of the designed system was validated by several experimental flights using a small fixed-wing UAV. To evaluate the validity of the proposed system, a set of special maneuvers was performed during test flights. It was found that even a simple feedforward artificial neural network could classify basic flight phases with very high accuracy and a limited set of three input parameters.
The automatization of particularly fast maneuvering aircraft has greatly reduced the sphere of man's scope by freeing him from routine operator work and moving it to the highest hierarchical level of the system. This forces aerospace manufacturers and users to address questions of a kind in a new way: how to design an ergatic system (ergatic system), how to optimize the coordination or human operator's entry into the "machine part", that has a distinctive feature of artificial intelligence. In this article, the properties of the ergatic system are investigated in order to determine the stability of the system in the longitudinal steady-state equilibrium flight mode at 22 965 ft, Mach 0.8, VTAS = 250 m/s. The Control System Toolbox, which is focused on solving tasks related to the analysis and synthesis of linear time - invariant dynamic systems, was used to solve the example. The basic prerequisite for the use of individual toolbox modules is knowledge mathematical models of controlled processes described in the state space, by means of transfer functions in s - area, z - area, time area, in the form of poles, zeros and amplification.
The automatization of particularly fast maneuvering aircraft has greatly reduced the sphere of man's scope by freeing him from routine operator work and moving it to the highest hierarchical level of the system. This forces aerospace manufacturers and users to address questions of a kind in a new way: how to design an ergatic system (ergatic system), how to optimize the coordination or human operator's entry into the "machine part", that has a distinctive feature of artificial intelligence. In this article, the properties of the ergatic system are investigated in order to determine the stability of the system in the longitudinal steady-state equilibrium flight mode at 22 965 ft, Mach 0.8, VTAS = 250 m/s. The Control System Toolbox, which is focused on solving tasks related to the analysis and synthesis of linear time - invariant dynamic systems, was used to solve the example. The basic prerequisite for the use of individual toolbox modules is knowledge mathematical models of controlled processes described in the state space, by means of transfer functions in s - area, z - area, time area, in the form of poles, zeros and amplification.
This article presents design and analysis of mathematical model UAV with fixed wings. The mathematical model serves to understand the basic mathematical principle and physical laws, that are applied to the system, and is indispensable in UAV movement simulation and modelling of the control algorithms. The article also describes the methodology of individual modelled parts using the XFLR5, where effective numerical methods are used for mathematical modelling. The last part provides verified and reliable results obtained by simulations of a mathematical model, which will be used to simulate basic and critical situation states.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.