Electric Servo Drive Control System of Milling Machine with Neural Network

Abstract

The article addresses mathematical description of a following cascade control system with a feed drive. A neural regulator is developed in Matlab-Simulink. This research compares application possibilities of a neural network regulator and an ordinary P-regulator. It also addresses the design process of a neural controller based on existing traditional regulators. During synthesis procedure, the neural regulator for stabilizing the speed of linear motion and compensation vibration occurring in the elastic elements of lathe machine’s feed drive is proposed. In this article several algorithms as Moller, Levenberg-Marquardt, Shelb-Ribira, gradient descent for training the neural regulator are compared. Comparative studies of several learning algorithms for creating neural controllers are provided.