Abstract
In this paper, a Hammerstein model based on forward feedback neural networks was proposed to tackle the optimal control of a nonlinear MISO system. The method offers a solution to the optimization of internal models. The optimal control with the preset value was implemented under both static and dynamic optimal indices. The simulation results showed that the algorithm can fulfill the task of blending ethanol and gasoline effectively.
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