Neural DMC Control Strategy for a CSTR in Presence of Noise

The prime objective of this work is to assess a neural DMC strategy in the case of experimental data corrupted with white noise. The neural DMC structure relies on the simple and innovative dynamic neural model recently developed. (Baratti et al., 2000). A nonisotbennal CSTR was cousidered as benchmark. The perfonnance of the DMC strategy was evaluated in terms of set-point tracking and disturbance rejection capabilities. The results show that the inaccuracy of the dynamic neural model is overcome by simply integrating the DMC structure with the available on-tine measurements even though they are corrupted with white noise.