This　paper　aims　to　tackle　two　complex　challenges　in　achieving　the　Nash　equilibrium　for　high-order　multiagent　systems　with　unknown　disturbances:　addressing　the　interconnection　issues　arising　from　the　high-order　systems,　and　mitigating　the　oscillations　caused　by　time-varying　unknown　disturbances.　To　address　such　challenges,　we　develop　a　distributed　adaptive　Nash　equilibrium　seeking　algorithm　utilizing　a　novel　state　observer　comprising　the　gradient　play　theory,　the　leader-following　consensus　protocol,　and　the　error　sign　function.　This　new　approach　not　only　achieves　the　seeking　of　the　Nash　equilibrium　but　also　effectively　accomplishes　the　goal　of　disturbance　suppression.　The　superiority　of　the　proposed　strategy　over　the　existing　seeking　schemes　lies　in　adopting　adaptive　feedback　in　the　strategy　design　process.　The　asymptotic　seeking　of　the　Nash　equilibrium　is　then　proved　by　using　the　input-to-state　stability　theorem　and　Barbalat　lemma,　and　sufficient　conditions　ensuring　the　convergence　are　developed.　Three　simulations　consisting　of　robots　with　mobile　sensor　networks,　the　three-order　multiagent　system,　and　the　energy　competition　within　power　generation　systems　are　conducted　to　illustrate　the　effectiveness　of　the　proposed　method.　©　2025