Individually-adapted Control and Support of Pilot's Control Actions Based on Neural Network Models
| Autor: | Veniamin N. Evdokimenkov, G. G. Sebryakov, O.N. Korsun, M. N. Krasil'shchikov, Moung Htang Om |
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| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Artificial neural network Computer science 010102 general mathematics Control (management) Process (computing) Control engineering 02 engineering and technology 01 natural sciences Course (navigation) Set (abstract data type) Aviation safety Precision approach radar 020901 industrial engineering & automation Path (graph theory) General Earth and Planetary Sciences 0101 mathematics Simulation General Environmental Science |
| Zdroj: | Procedia Computer Science. 103:126-134 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2017.01.028 |
| Popis: | The report presents the concept of intelligent monitoring and support for pilot control activities when performing an aircraft landing modes. The approach uses a neural network model of the system aircraft-pilot. It is supposed that the model is unique for every pilot. This model is continuously updated in the process of pilot activities according to the results of all previous flights, and reflects the individual manner of controlling the aircraft specific to this very pilot. This approach provides the greater forecast accuracy of the aircraft path while performing a landing. The forecast is used to generate the support signals to the pilot in order to increase the landings accuracy. The report also presents the results of testing the developed neural network model at the set of data obtained using a modern aircraft simulation facility. The report also discusses the use of the individual neural network model of the pilot for generating optional indicating signals to diminish course and glide path deviations while performing the landing. |
| Databáze: | OpenAIRE |
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