Abstract
An optical stabilization of UAV (UAS) is a very important part of a structure in their control systems. Not only as a backup stabilization system in a case of IMU failure, but also as a main system, used for stabilization or navigation. In this paper the concept of a system for environment character detection is presented. The system can classify a surrounding environment depending on chosen characteristics. Such system can be used for a better horizon detection due to switching to a correct horizon detection algorithm, which can be used for determining the position of UAV. The system is based on Takagi - Sugeno fuzzy inference system and fuzzy artificial neural networks. An earlier work on this subject was presented last year, but concept of the system was redesigned with a usage of fuzzy artificial neural network for a more precisive outputs and automatic determination of characteristics of fuzzy sets on input.
Highlights
Magnetic fields are vector quantities characterized by both strength and direction
Electromagnetic inferences lead to an uncontrolled movements of UAV in a case of algorithm failure
Drift of UAV, for example small helicopter, can lead to PID controller oscillations which can cause an uncontrolled movements in area of five meters and more radius
Summary
Magnetic anomalies - such as a storm, electric wiring, electric trains. Electromagnetic pulse, intentional interferences. Magnetic anomalies - such as a storm, electric wiring, electric trains. An inertial measurement unit (IMU) is an electronic device that measures and reports a craft velocity, orientation, and gravitational forces, using a combination of accelerometers and gyroscopes, sometimes magnetometers. For the reasons mentioned above, the need for a backup system is obvious, especially for UAV. Unlike normal airplanes and helicopters, which can be controlled by a human pilot in a case of sensor failure, the autonomous UAV do not have such an option
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