NLq neural control theory: Case study for a ball and beam system

In this paper we design a linear dynamic output feedback controller for a ball and beam system based on an identified neural state space model. This is done by applying dynamic backpropagation, constrained by NL
q
internal or I/O stability conditions. The performance of the controller has been tested on a real ball and beam set-up.