M-estimation　is　a　widely　used　technique　for　robust　statistical　inference.　In　this　paper,　we　study　robust　partially　functional　linear　regression　model　in　which　a　scale　response　variable　is　explained　by　a　function-valued　variable　and　a　finite　number　of　real-valued　variables.　For　the　estimation　of　the　regression　parameters,　which　include　the　infinite　dimensional　function　as　well　as　the　slope　parameters　for　the　real-valued　variables,　we　use　polynomial　splines　to　approximate　the　slop　parameter.　The　estimation　procedure　is　easy　to　implement,　and　it　is　resistant　to　heavy-tailederrors　or　outliers　in　the　response.　The　asymptotic　properties　of　the　proposed　estimators　are　established.　Finally,　we　assess　the　finite　sample　performance　of　the　proposed　method　by　Monte　Carlo　simulation　studies.