The basis of the paper is that there are already some methods to accurately evaluate, test and diagnose the performance of the model predictive controller. And the result shows the reason of a bad performance of control system is because of model mismatch. There are much more complexity and variety in the problem of multiple mismatched parameters than single mismatched parameter, so we need consider more factors about it on the basis of the solution of single mismatched parameter. We propose a way of adjusting model parameters based on fuzzy rules when there are more than one mismatched parameters. The method is to adjust the step-size of parameters and get the adjustment rules on the basis of the changes of maximum overshoot, rising time and settling time. The last, verifying the method is effective by experiments.

Hydrometallurgy is a popular metallurgical technology. Filter press is common but vital to the production of hydrometallurgy. Hence, the process monitoring of filter press is of great significance for hydrometallurgy. Due to data analysis and related knowledge of filter press, Principal component analysis (PCA) is applied to process monitoring of the filter press via two traditional statistics. However, modeling and test data collected from actual production suffers from outliers, missing data, inconsistent sampling period between variables. Based on these practical problems, corresponding data proceeding technique is proposed. The final application simulation illustrates the validity of the proposed method.

The pickling process is the important metallurgical production process. Based on pickling process prediction model, considering the max economic efficiency as the optimized objective, and seeing the operating variables as the decision variables, this paper establishes the pickling process optimization model and makes the optimized calculation to get the value of each key control circuit. At the same time, considering the pickling process prediction model error brings the uncertainty to the optimization results, based on iterative optimization control thoughts do pickling process optimization control, the simulation results verify the effectiveness of the method.