The conventional PID control has
been proven insufficient and incapable
for this particular petro-chemical process. This paper proposes a
nonlinear adaptive predictive functional control (NAPFC) algorithm
based on the Takagi–Sugeno (T-S) model for average cracking
outlet temperature (ACOT) of the ethylene cracking furnace. In this
algorithm, in order to overcome the effect on system performance under
model mismatch, the structure parameters of the T-S fuzzy model are
confirmed, and the model consequent parameters are identified online
using the forgetting factor least-square method. Prediction output
is calculated according to the identified parameters instead of computing
the Diophantine equation, thereby obtaining directly the predictive
control law and avoiding the complex computation of the inverse of
the matrix. Application results on ACOT of the ethylene cracking furnace
show the proposed control strategy has strong tracking ability and
robustness.
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