A　fuzzy　programming　through　stochastic　particle　swarm　optimization　is　developed　for　the　assessment　of　filter　allocation　and　replacement　strategies　in　fluid　power　system　(FPS)　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.　As　the　simulation　results　indicate,　the　developed　model　can　successfully　decrease　the　total　cost　and　enhanced　the　safety　of　system.　Generally,　it　is　believed　that　the　model　can　help　identify　excellent　filter　allocation　and　replacement　strategy　with　minimized　operation　cost　and　system　failure　risk　while　protecting　the　system.