Study on the Synthetic Optimization Control of Information Incomplete Complex Industrial Process

The paper, started with the solution of permeability-state and BTP (Burning Through Point)-state optimization in the information incomplete, long time-delay complex sintering process, has proposed the neural network-based predictive model and the state-optimization algorithm under the comparative stable status. It includes the state values optimization algorithm with experts rules, the clustering parallel grid optimization algorithm, thus the state optimization of Lead-Zinc sintering process can be turned into a multi-constrained, multi-target, nonlinear optimization issue. The fuzzy expert control participated by operators is used for the state optimization under the serious fluctuation status. Finally, with the defuzzification synthetic optimization, the results of the two control methods are combined to improve the stability and industrial effectiveness of the control system.