Selection of input and output variables as a model reduction problem

The procedure for selecting input and output variables, proposed by Keller and Bonvin [4] is analysed using the principle of internal dominance proposed by Moore [6]. Using that principle, a dominance condition for the subsystem of the selected variables over the subsystem of the neglected variables is derived. It can be shown that the proposed variable selection procedure maximizes the dominance of the subsystem of the selected variables, hence justifying the proposed selection. The investigation further shows that prior model reduction can significantly improve variable selection since it eliminates the negative effects of inappropriate modelling.