Login
Register
Reset Password
Publish & Distribute
Publishing Solutions
Distribution Solutions
Subjects
Architecture and Design
Arts
Business and Economics
Chemistry
Classical and Ancient Near Eastern Studies
Computer Sciences
Cultural Studies
Engineering
General Interest
Geosciences
History
Industrial Chemistry
Jewish Studies
Law
Library and Information Science, Book Studies
Life Sciences
Linguistics and Semiotics
Literary Studies
Materials Sciences
Mathematics
Medicine
Music
Pharmacy
Philosophy
Physics
Social Sciences
Sports and Recreation
Theology and Religion
Publications
Journals
Books
Proceedings
Publishers
Blog
Contact
Search
EUR
USD
GBP
English
English
Deutsch
Polski
Español
Français
Italiano
Cart
Home
Journals
Transactions on Aerospace Research
Volume 2024 (2024): Issue 1 (March 2024)
Open Access
Study of Stability Criteria of Automatic Control Systems By Multiparametric Aviation Objects
Volodymyr Zinovkin
Volodymyr Zinovkin
,
Iurii Krysan
Iurii Krysan
,
Andrii Pyrozhok
Andrii Pyrozhok
and
Taras Yanko
Taras Yanko
| Mar 13, 2024
Transactions on Aerospace Research
Volume 2024 (2024): Issue 1 (March 2024)
About this article
Previous Article
Next Article
Abstract
Article
Figures & Tables
References
Authors
Articles in this Issue
Preview
PDF
Cite
Share
Article Category:
research article
Published Online:
Mar 13, 2024
Page range:
45 - 70
Received:
Jan 24, 2022
Accepted:
Jan 08, 2024
DOI:
https://doi.org/10.2478/tar-2024-0004
Keywords
control system
,
aviation object
,
optimisation
,
stability
,
mathematical model
,
modelling
© 2024 Volodymyr Zinovkin et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Fig. 1.
The structural diagram of the flying object’s control system with multiple parameters of a different physical nature. The following designations are accepted in Fig. 1: TT – technical requirements; TK – request for proposal; P – electromechanical actuating mechanisms; N – hydraulic and pneumatic actuating mechanisms; S – thermal and traction mechanisms; Z – mechanisms of attitude control; K – mechanisms of the current thermal state; BCTI – block of current technical information (in respect to the actuators condition); CICU – current information converting unit; SOCD – software-optimisation and control device; CS – corrected signal; DT – directive task of actuators nominal parameters; FO – flying object; VCI – visualisation of current information; BSI – block for saving all information; BREM – unit of recording changing parameters of the corresponding actuators.
Fig. 2.
Physical model of the flying object in one of its positions in space. The following designations are accepted in the Fig. 2: 1 – remote control; 2 – microprocessor module; 3 – power block; 4 – booms; 5 – airplane flaps; 6 – airplane propeller; 7 – rudder; and 8 – elevators.
Fig. 3.
Structural diagram of solving high-order systems with a limited input coordinate of the problem, which provides optimal stability of the control system of flying objects with multiple parameters of a different physical nature. The following designations are accepted in Fig. 3: 1 – directive task; 2 – the first level of the differentiator; 3 – the second level of the differentiator; 4 – nonlinear converter that produces a proportional signal φ(y, z); 5 – the resulting optimal signal; and 6 – actuating mechanism.
Fig. 4.
Structural diagram of modelling the stability of the control system by flying objects. The following designations are accepted in Fig. 4: 0 – library of the directive task and nominal data of actuating mechanisms; 1 – driver of the limits of accuracy and error; 2 – driver of digital information and coordination of information channels; 3 – amplifier and coordinator of microprocessor-based and software devices; 4 – correcting device or regulator; 5 – working out of executive mechanisms to a new level; 6 – monitoring of changes or deviations of actuators parameters and technical condition of the object being controlled.
Fig. 5.
Structural diagram for solving a differential equation using the method of reducing the order of the derivative.
Fig. 6.
Simulated graph of the Mikhailov hodograph.
Fig. 7.
Nyquist hodograph.
Fig. 8.
Refined graph of the system stability according to the Nyquist hodograph.
Preview