Application of neural networks to the flexible pole-cart balancing problem

This paper investigates the use of neural networks in the control of highly nonlinear systems. Online and off line control of a cart balancing a flexible pole under its first mode of vibration using neural networks is presented. Backpropagation and Kohonen's self-organizing map have been used as neural network examples. The networks learned from a set of training data derived from a real system and were initially tested against a computer simulation of the derived dynamics of the flexible pole-cart balancing system and then applied to the real system.