NEURO-SYSTEM OF AIMING AND STABILIZING WITH A REGULATOR ON THE BASIS OF STANDARD MODEL MODEL REFERENCE CONTROLLER

Authors

  • B. I. Kuznetsov State Institution "Institute of Technical Problems of Magnetism of the NAS of Ukraine", Ukraine https://orcid.org/0000-0002-1100-095X
  • T. E. Vasilets Ukrainian Engineering Pedagogics Academy, Ukraine
  • O. O. Varfolomiyev New Jersey Institute of Technology, United States

DOI:

https://doi.org/10.20998/2074-272X.2015.4.06

Keywords:

neural network control, aiming and stabilization system, nonlinear dynamic object, neuro-controller on the basis of standard model, Model Reference Controller

Abstract

The aim of this work is the synthesis of neural network aiming and stabilization system for the special equipment of moving objects with neuro-controller on the basis of standard model and performance comparison of the neural network system with the neural network predictive control. Build a block diagram of the neural network aiming and stabilization system, based on the subject control principle with PD-regulator in the position loop and with neuro-controller on the basis of standard model in the in the velocity loop. The neuro-controller on the basis of standard model Model Reference Controller is synthesized in the MATLAB Neural Network Toolbox and system simulation is performed. The studies show that the transient state variables of the system are oscillatory. Therefore, the neuro-controller with the prediction NN Predictive Controller should be used for aiming and stabilizing system to provide high dynamic characteristics achieved at the cost of higher complexity and computational cost.

Author Biography

B. I. Kuznetsov, State Institution "Institute of Technical Problems of Magnetism of the NAS of Ukraine"

д.т.н., профессор, отдел проблем управления магнитным полем

References

Terekhov V.A., Yefimov D.V., Tyukin I.Yu. Nejrosetevye sistemy upravlenija [Neural network control system]. Moscow, IPRZhR Publ., 2002. 480 p. (Rus).

Rudenko O.G., Bodyansky E.V. Shtuchni nejronni merezhi: Navchal'nyj posibnyk [Artificial Neural Networks: Tutorial]. Kharkov, TOV «Kompanіja SMІT» Publ., 2006. 404 p. (Ukr).

Kuznetsov B.I., Vasilets T.E., Varfolomiyev O.O. Development of a neuro-system of guidance and stabilizing for light-armored machines armament. Elektrotekhnіka і elektromekhanіka – Electrical engineering & electromechanics, 2008, no.2, pp. 31-34. (Rus).

Kuznetsov B.I., Vasilets T.E., Varfolomiyev O.O. Synthesis of a predictive neuro-controller for a two-mass electromechanical system. Elektrotekhnіka і elektromekhanіka – Electrical engineering & electromechanics, 2008, no.3, pp. 27-32. (Rus).

Kuznetsov B.I., Vasilets T.E., Varfolomiyev O.O. Nonlinear dynamic object neuro-control using a generalized predictive control method. Elektrotekhnіka і elektromekhanіka – Electrical engineering & electromechanics, 2008, no.4, pp. 34-41. (Rus).

Kuznetsov B.I., Vasilets T.E., Varfolomiyev O.O. Synthesis and study of the light armored vehicle aiming and stabilization system with neural network control based on the autoregressive-moving-average model. Sistemi ozbroennya i viyskova tehnika – Systems of arms and military equipment, 2010, no.4(24), pp. 118-121. (Ukr).

Published

2015-08-28

How to Cite

Kuznetsov, B. I., Vasilets, T. E., & Varfolomiyev, O. O. (2015). NEURO-SYSTEM OF AIMING AND STABILIZING WITH A REGULATOR ON THE BASIS OF STANDARD MODEL MODEL REFERENCE CONTROLLER. Electrical Engineering & Electromechanics, (4), 35–39. https://doi.org/10.20998/2074-272X.2015.4.06

Issue

Section

Electrotechnical complexes and Systems

Most read articles by the same author(s)

1 2 > >>