Wu Y.-J.,Key Laboratory of Process Industry Automation |
Wu Y.-J.,Northeastern University China |
Wu Z.-W.,Key Laboratory of Process Industry Automation |
Wu Z.-W.,Northeastern University China |
And 3 more authors.
Xitong Fangzhen Xuebao / Journal of System Simulation | Year: 2011
The electro-fused magnesia furnace is one of the main equipments which is used to produce electro-fused magnesia. The process has integrated complexities, such as strong coupling, nonlinearity and large time delay. To validate the intelligent decoupling control of them, a distributed simulation platform was established. The simulation platform consists of Programmable control systems (PLC), virtual instruments and actuators, and a plant computer which is acted as the virtual process. On the plant computer, the input-output dynamics of the electro-fused magnesia furnace was simulated by the interaction seamlessly between MATLAB and DotNet programming platform. All signals of the platform are accordance with those of real industrial processes. Experiment results show that the intelligent optimization control algorithms can be validated by the platform in the view of engineering. Source
Wenlei Z.,Northeastern University China |
Wenlei Z.,Key Laboratory of Process Industry Automation |
Jiapeng Y.,Northeastern University China |
Jiapeng Y.,Key Laboratory of Process Industry Automation |
And 2 more authors.
Key Engineering Materials | Year: 2011
Product variation and customization is a trend in current market-oriented manufacturing environment. Product configuration is the key technology in this customization environment. But complex customer requirements are still hard to resolve. So the purpose of this study is to offering a new intelligent configuration algorithm to this problem, which is based on Product Family Genealogy Model (PFG). Characteristics of customer group, modules and product platform are discussed to build a PFG model - a hierarchy of reasonable configuration models. Based on it, both the customer requirements and constraints are classified and treated respectively. So the product configuration task can be easily accomplished by four sequenced stages i.e. "PFG position", "key configuration", "basic configuration", and "form configuration". Finally, an example of desktop configuration is presented to demonstrate this approach. Source
He D.,Northeastern University China |
He D.,Key Laboratory of Process Industry Automation |
Zhao Y.,Northeastern University China |
Zhao Y.,Key Laboratory of Process Industry Automation |
And 4 more authors.
Journal of Computational Information Systems | Year: 2010
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. Copyright © 2010 Binary Information Press May, 2010. Source