Reduced Diophantine predictors for long range predictive controllers

New reduced Diophantine predictors are developed which are mathematically equivalent to the conventional predictors used in long range predictive controllers (LRPC´s) such as GPC. In adaptive applications they result in computational savings of up to 65%. The new formulations are also much simpler, do not require filtered input and output values, and lead to new insight and interpretations of LRPC´s. Two theorems with proofs are included which establish the equivalence of the new and the conventional LRPC´s formulations