Interaction Balance Method for Large-scale Industrial Processes With Fuzzy Constraints

Abstract

The interaction balance method (IBM) with fuzzy constraints is proposed for large-scale industrial processes under hierarchical steady-state optimization with the consideration of the model-reality difference and the constraints of subprocesses being flexible. In this approach, the models that are treated as equality constraints and the inequality constraints of the subprocesses are all fuzzified. Two cases of interaction balance method are studied: the open-loop IBM and the IBM with global feedback. Simulation results show that the solutions of the proposed method with global feedback are very close to the optimal solutions of the real process.