Neural network-based optimal control of a DC motor positioning system

Maksym Khomenko and Volodymyr Voytenko

Industrial Electronics Department,

Chernihiv State Technological University,

95 Shevchenko Street,

Chernihiv, 14027, Ukraine



Yuriy Vagapov*

Department of Engineering and Applied Science,

Glyndwr University,

Plas Coch, Mold Road,

Wrexham, LL11 2AW, UK


*Corresponding author

Abstract: This article describes an optimal control algorithm for a DC motor drive operating as a positioning system. The control algorithm is based on combination of artificial neural network and state space method with variable gain. The positioning system operating under proposed algorithm has demonstrated a transient process close to optimal without overshoot. It has been also shown that the control algorithm is robust to the change of the DC motor parameters and the supply voltage disturbances. An experimental setup based on TMS320F243 evaluation module has been designed and built in order to prove the simulation results. The algorithm has been verified by simulation using MATLAB/Simulink and proved by a number of practical experiments.

Keywords: DC electric drives; positioning systems; artificial neural network; ANN; digital control.

Reference to this paper should be made as follows:

Khomenko, M., Voytenko, V. and Vagapov, Y. (2013) ‘Neural network-based optimal control of a DC motor positioning system’, Int. J. Automation and Control, Vol. 7, Nos. 1/2, pp.83–104.