Research Of Multivariable System Adaptive Fuzzy Control Based On Fieldbus

Dealing with control problem in complex industry process with large time delay, nonlinear, multi-variable, to develop intelligent control is an available way. Industrial Ethernet and fieldbus technology has been widely used in the production of the modern enterprise. Research in the industrial network environment to achieve effective control of complex systems, is the research focus of the current control area, with a wide range of applications.This paper selects the electric furnace that is used to test aircraft high-temperature alloys on the "high-temperature persistent testing machine" as control object, characterized with large time delay, nonlinear, unidirectional, asymmetric coupling. According to the characteristics of the electric furnace, the membership function of input and output lingual variables and control rules are formed in this thesis. Then, in order to overcome the limitation of the traditional fuzzy control, a kind of adaptive fuzzy controller is designed in which the fuzzy regulator is used to online tune the three parameters of the traditional fuzzy control system, and improved ant colony algorithm is introduced to optimize the fuzzy control rules. Simulation experiment has been done, and compared with traditional fuzzy control. The research results provide effective data and parameters for the actual electric furnace control.Based on the simulations, the paper implements designed adaptive fuzzy controller to carry out the temperature control of actual electric furnace in fieldbus control system. The SIEMENS FCS hardware platform is used. As for the small memory problem of SIEMENS industrial controllers (CPU 317-2 PN/DP), the complex task is decomposed into independent function block that is executed by the main loop module to make control easier, and WinCC that is SIEMENS configuration software shows the system operation and monitoring interface. According to the experiments, the control effects of adaptive fuzzy control and traditional fuzzy control have been analyzed and contrasted to each other. The results demonstrate that designed adaptive fuzzy controller has a favorable quality of control.