Development of control systems for movement mechanisms of electric drives based on neural networks

Abstract

The paper presents the results of the development and investigations of intelligent control systems for electric drives of DC and AC movement mechanisms. It is shown that the use of methods of genetic algorithms for training and structural optimization of neural systems makes it possible to synthesize the control law excluding the self-oscillating process arising from the nonlinearity of the "friction pair" type load. The developed systems have a single easily realizable feedback on the speed of the motor which does not create difficulties in physical realization.