Neural network based system modeling

A method of using multi-layer perceptrons (MLPs) for modeling complex nonlinear systems is investigated. The importance of pre-processing is crucial to the modeling stage. This includes classifying input/output data into different categories for training-data selection, as well as extracting key features of the data. In this paper a prototype problem, an inverted pendulum system, is simulated as a physical system to be identified. The discussion focuses on this problem although the ideas are generic.