On the invertibility of the RBF model in a predictive control strategy

This paper describes the importance of the RBF model quality in a model-based predictive control scheme. We show that a good neuronal approximator does not necessarily correctly model the intrinsic behaviour of the identified system. We have used a simulated example to show the harmful effects of a particular type of incorrect behaviour, the non-invertibility of the model relative to the control input. Lastly, we propose a derived RBF model that is slightly more complex, but which is systematically invertible.