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Title: APPLICATION OF NEURAL FUZZY CONTROL TO ADAPT THE PHYSICAL LAYER OF A FLYING SENSOR NETWORK
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APPLICATION OF NEURAL FUZZY CONTROL TO ADAPT THE PHYSICAL LAYER OF A FLYING SENSOR NETWORK
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1314-2704
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English
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20
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2.1
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Modern unmanned aerial vehicles (UAVs) are used to perform a wide range of flight
tasks (military and civil), implemented both in autonomous flight mode and by remote control. One of the advanced technologies for their use is the organization of flying sensor networks (FSN). The quality of information exchange in FSN, widely used for monitoring of various natural and technical objects, depends significantly on the conditions of signal propagation and the level of external interference. A promising method for improving FSN performance is to adapt the transmission mode depending on the signal-to-noise ratio at the input of UAV receivers, namely, changing the encoding speed and modulation method. To adapt the physical level of the flying sensor network, it is proposed to use a hybrid method of network management based on artificial neural networks (ANN) and fuzzy logic. For practical implementation of the proposed approach, a functional scheme of a closed automatic control system with negative feedback for the receiving and transmitting module of UAV radio transmitters is proposed. The scheme is based on a fuzzy controller with an auto-tuning unit based on an artificial neural network with a single hidden layer. This functional scheme of the automatic control system of the physical layer of the OSI network model for the receiving and transmitting module of UAV radio transmitters can be built on the basis of all possible known variants of controllers (proportional P, integral I, proportionalintegral PI, differential D, PID, etc.). The fuzzy controller is synthesized using the Takagi-Sugeno fuzzy inference algorithm. |
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conference
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20th International Multidisciplinary Scientific GeoConference SGEM 2020
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20th International Multidisciplinary Scientific GeoConference SGEM 2020, 18 - 24 August, 2020
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Proceedings Paper
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STEF92 Technology
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International Multidisciplinary Scientific GeoConference-SGEM
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SWS Scholarly Society; Acad Sci Czech Republ; Latvian Acad Sci; Polish Acad Sci; Russian Acad Sci; Serbian Acad Sci & Arts; Natl Acad Sci Ukraine; Natl Acad Sci Armenia; Sci Council Japan; European Acad Sci, Arts & Letters; Acad Fine Arts Zagreb Croatia; C
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33-40
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18 - 24 August, 2020
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website
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cdrom
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6966
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unmanned aerial vehicles; flying sensor networks; OSI network model;
physical layer; adaptation; artificial neural networks; regulators; fuzzy logic; modulation; coding. |
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