By　considering　the　uncertainties　existing　in　engineering　structures,　the　parameter　identification　using　probabilistic　methods　may　provide　more　reliable　predictions.　However　sufficient　probabilistic　information　of　a　structure　is　often　impractical　in　the　real　world.　Moreover,　sometimes　engineers　require　only　the　limits　of　parameters　and　responses.　Due　to　these　facts,　the　application　of　interval　analysis　for　parameter　identification　could　be　more　rational.　This　study　develops　a　new　concept　of　interval　response　surface　model,　which　incorporates　the　conventional　response　surface　model　with　the　interval　arithmetic.　The　expression　of　the　response　surface　is　first　transformed　into　a　complete-square　form　and　then　interval　variables　are　introduced　into　the　transformed　expressions.　By　this　means,　the　usual　interval　overestimation　due　to　interval　arithmetic　operations　can　be　avoided　providing　correct　interval　predictions.　Secondly,　the　infimum　and　supremum　of　interval　parameters　are　used　to　construct　the　objective　functions　for　interval　inverse　optimization.　Then　using　the　interval　response　surface　models,　the　interval　model　updating　procedure　is　implemented.　The　proposed　method　can　avoid　the　complicated　sensitivity　computation　of　interval　parameters　and　thus　highly　simplifies　the　interval　model　updating　process　in　the　interest　of　improving　the　updating　efficiency.　Lastly,　the　proposed　method　has　been　validated　using　a　numerical　mass-spring　system　and　then　a　set　of　experimental　steel　plates.　The　intervals　of　their　geometric　and　material　parameters　are　identified　and　the　updating　results　have　proved　the　feasibility　and　reliability　of　the　method.　©,　2015,　Nanjing　University　of　Aeronautics　an　Astronautics.　All　right　reserved.