| With the continuous development of modern network communication,automation and other technical fields,the industrial control system structure is undergoing a process from cen-tralized control to distributed control.The intelligent,networked new industrial model pro-posed by "Industry 4.0" is affecting industrial systems worldwide.This paper combines the current mainstream heterogeneous collaborative computing model thinking,innovatively un-der the premise of given physical resource constraints,how to generate a population model with collaborative heterogeneous computing capabilities.In the actual research on multi-machine,multi-module collaborative heterogeneous agent control system,we find that the scheduling constraint relationship of equipment physical resources in the system is the key factor affecting the control ability of heterogeneous systems.This is a key factor influencing and constraining the decomposition of complex models.We use the complex model as the research object,and decompose the model based on the formalization method of program slicing technology and system dependency graph to generate the corresponding group model,and then study the syn-ergy relationship between the group sub-models to obtain the field of industrial control.Group synergy model.The main work of this paper is summarized as follows:1.An event-driven modeling language IMCL that can describe heterogeneous system re-sources is designed.The language can put all the different physical resources into the unified industrial control system abstract model.On the basis of platform independence,we can de-scribe the complex industrial control system into a complex model of language form by studying the control logic of the system..2.This study proposes a resource-constrained model decomposition technique,which in-novatively studies the constraint relationship between controller and physical resources,and relies on the formalized program decomposition principle to propose a method that can auto-matically complicate a complex The model is decomposed into decomposition algorithms for multiple submodels.The decomposition algorithm intelligently decomposes all physical device resources in a complex system into corresponding models according to the constraint relation-ship,thereby forming a group model.3.In order to ensure that the decomposed group sub-models can cooperate with each other,we compare the decomposed model with the original model,and study the synergistic relation-ship with the original system's control logic dependency and data dependency constraint.A communication coordination mechanism based on the formal method is added to the decom-posed model,so that the internal sub-models of the group model can be consistent with the overall data control and logic control through the communication coordination guarantee and the original model system diagram,and finally the group model is guaranteed.And the original complex model is functionally equivalent.In this study,it is through the scientific modeling of the functional characteristics of com-plex industrial systems,using formal thinking to analyze the constraints and system character-istics within complex models,and thus to study the population model generation technology.In the end,it not only improves the reliability and safety of the industrial control system develop-ment process,but also provides new development methods for development designers,refines the design process of complex systems,and improves development quality and efficiency. |
