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Design of an analytic constrained predictive controller using neural networks

By: Botto, Miguel Ayala; van den Boom, Ton J.J.; Hoekstra, Peter;

2001 / IEEE


This item from - IEEE Conference - 2001 European Control Conference (ECC) - The solution to the standard predictive control problem is a continuous function of the state, the reference signal, the noise and the disturbances and hence can be approximated arbitrarily close by a feed-forward neural network. This leads to an analytic constrained predictive controller that combines constraint handling with speed and is applicable to fast systems and complex control problems with many constraints.