Abstract:

A complex exothermic batch reactor model was developed by using structure approaching hybrid neural networks（SAHNN）. The optimal reactor temperature profiles were obtained via the PSO-SQP algorithm solving maximum product concentration problem based on recurrent neural network（RNN）.Considering model-plant mismatches and unmeasured disturbances，a novel extended integral square error index（EISE）was proposed，which introduced mismatches of model-plant into the optimal control profile. The approach used a feedback channel for the control and therefore dramatically enhanced the robustness and anti-disturbance performance. The stability analysis of the one-step-ahead control strategy through SAHNN-based model was described based on Lyapunov theory in detail. The result fully demonstrated the effectiveness of the proposed optimal control profile.