Oxygen　content　in　flue　gas　is　an　important　process　parameter　for　incineration　efficiency　in　municipal　solid　waste　incineration　(MSWI).　Due　to　the　complexity　of　municipal　solid　waste　incineration　process,　it　is　difficult　to　achieve　effective　control　of　oxygen　content　in　flue　gas　in　practical　application.　A　data-driven　adaptive　predictive　control　method　for　oxygen　content　in　flue　gas　in　MSWI　process　is　proposed　in　this　paper.　Firstly,　an　adaptive　fuzzy　C-means　(FCM)　algorithm　is　used　to　determine　the　number　of　hidden　layer　neurons　and　the　initial　clustering　center　of　radial　basis　function　(RBF)　neural　network　model,　and　the　radial　basis　function　neural　network　prediction　model　based　on　FCM　algorithm　is　established.　During　the　control　process,　the　prediction　model　parameters　are　adjusted　adaptively　by　an　online　updating　strategy.　Then,　the　gradient　descent　method　is　exploited　to　solve　the　control　law,　and　the　stability　of　the　control　system　is　analyzed　based　on　the　Lyapunov　theory.　Finally,　the　effectiveness　of　the　proposed　control　method　is　verified　based　on　the　actual　data　of　the　municipal　solid　waste　incineration　plant.　©　2023　Science　Press.　All　rights　reserved.