An experimental approach to the control of electrical drives by use of a progressive learning neural network

This paper describes the laboratory implementation of a control of a DC drive based on a progressive learning neural network (PLN). The objective is to verify the goodness of this network in the so-called direct inverse control with generalized learning. After describing the fundamentals of PLN and the control strategy, the test bed is presented. Then the experimental results are discussed.