Development of hybrid intelligent optimal-setting control system for IMSP based on .NET component technology

The closed-loop optimal control of the technical indices for intensity magnetic separation process (IMSP) is difficult to realize since the fact that the indices cannot be measured continuously online. To solve this problem, an intelligent optimal setting controller, which consists of case-based reasoning (CBR) pre-set module, wavelet neural network (WNN) soft-sensor module and rule-based reasoning compensator, is designed with the integration of the process knowledge, expert experience and process data. In view of the drawback of the existing optimization control software system, such as lower degree of standardization, poor scalability and reusability of resources, a magnetic separation optimal setting control software system, which integrates optimization control and operation monitoring function, is designed and developed based on .Net component technology. This system supports three kinds of algorithm, i.e., dynamic link library, Matlab script and VBScript script, according to different people which have different program skills. The simulation experiments at hardware-in-loop simulation platform demonstrate that the system can guarantee product quality for IMSP under certain robustness.