Generalized Dynamic Constraints Network Based on Simulation and Knowledge

In view of uncertainty of parameters in concurrent and collaborative design,the constraints network is extended to the generalized dynamic constraints network (GDCN) to cope with the uncertainty trouble.First,the model of GDCN including both the domain level and knowledge level constraints is established.Second,the effective method to represent the domain constraints based on simulation results and adaptive response surface approach is introduced,and a data-mining algorithm named fuzzy-rough sets algorithm is developed to mining the knowledge constraint from the numerical simulation data.Then,the unified expression of constraints in GDCN is worked out with template approach,and the clearing up strategy of conflicts among constraints is presented to gain consistent parameter intervals.A design example is illustrated to show effectiveness of this proposed method.