An improved fuzzy programming model with an L—R fuzzy number for filter management strategies in fluid power systems under uncertainty

Abstract

A fuzzy non-linear programming model is developed for the assessment of filter allocation and replacement strategies in fluid power systems (FPSs) under uncertainty. It can not only handle uncertainties expressed as L—R fuzzy numbers, but also enhance the system robustness by transforming the fuzzy inequalities into inclusive constraints. In modelling formulation, theory of contamination wear is introduced to reflect the interactions between system performance and system contamination level. The developed method has been applied to the planning of filter allocation and replacement for an FPS with a bypass filtration system, and a piecewise linearization approach is proposed for solving model non-linearities. Three different contaminant ingression rates are examined based on a number of filter-installation scenarios. The generated solutions can be used for providing guidance to decision makers to identify better contamination control plans for achieving a minimized system cost and system-failure risk.

Keywords

contaminant sensitivity decision making fluid power system L—R fuzzy number optimization

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