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Algorithms of constructing a neural network model for a dynamic object of control and adjustment of PID controller parameters

  • Flight Dynamics and Control of Flight Vehicles
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Abstract

The paper presents an algorithm for constructing a neural network model for a dynamic object of control based on the data sample obtained as a result of the object operation. The algorithm being considered applies a neural network approach and a genetic algorithm. An algorithm is presented for determining a domain of possible values for a proportional-integral-derivative controller (PID controller) based on application created neural network model of the controlled object.

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Authors and Affiliations

  1. Tupolev Kazan National Research Technical University, Kazan, Russia

    L. Yu. Emaletdinova & E. D. Tsaregorodtseva

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  1. L. Yu. Emaletdinova
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  2. E. D. Tsaregorodtseva
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Original Russian Text © L.Yu. Emaletdinova, E.D. Tsaregorodtseva, 2013, published in Izvestiya VUZ. Aviatsionnaya Tekhnika, 2013, No. 3, pp. 27–33.

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Emaletdinova, L.Y., Tsaregorodtseva, E.D. Algorithms of constructing a neural network model for a dynamic object of control and adjustment of PID controller parameters. Russ. Aeronaut. 56, 247–256 (2013). https://doi.org/10.3103/S1068799813030069

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  • DOI: https://doi.org/10.3103/S1068799813030069

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