An　interval-fuzzy　quadratic　programming　(IFQP)　method　is　developed　for　the　assessment　of　filter　allocation　and　replacement　strategies　in　fluid　power　systems　(FPS)　under　uncertainty.　It　can　directly　handle　uncertainties　expressed　as　interval　values　and/or　fuzzy　sets　that　exist　in　the　left-hand　and　right-hand　sides　of　constraints,　as　well　as　in　the　objective　function.　Multiple　control　variables　are　used　to　tackle　independent　uncertainties　in　the　model＇s　right-hand　sides　and　thus　optimize　the　overall　satisfaction　of　the　system　performance.　The　IFQP　method　is　applied　to　a　case　of　planning　filter　allocation　and　replacement　strategies　under　uncertainty　for　an　FPS　with　a　single　circuit.　A　piecewise　linearization　approach　is　firstly　employed　to　convert　the　nonlinear　FPS　problem　into　a　linear　one.　The　generated　decision　alternatives　can　help　decision　makers　to　identify　desired　policies　for　contamination　control　under　various　total　costs,　satisfaction　degrees,　and　system-failure　risks　under　different　contaminant-ingression/generation　rates.