Differential evolution algorithm based on interaction prediction method for large-scale industrial processes of fuzzy mode
As a result of slow perturbations, the mathematical model of an actual system is difficult to be accurate. So when optimizing large-scale industrial process, the mathematical model and the actual system does not match, that is model-actual difference. Large-scale industrial process optimization based on fuzzy model is an effective way of this issue. However, the optimization model is the process of establishing a non-linear programming model. So, the differential evolution algorithm is studied in this paper to solve the problems of large-scale industrial processes optimization based on fuzzy models. The mainly method is to solve fuzzy nonlinear programming problem. Firstly the differential evolution algorithm is proposed to solve fuzzy nonlinear programming problems. Then the combination of fuzzy nonlinear problems and the interaction prediction method (shorts for IPM) of large-scale industrial processes is introduced. Lastly, simulation show the validity of the method which is proposed in this paper.
Author's Name: He, D., Zhao, Y., Wang, L., Chang, H.