Precise　control　of　furnace　temperature　(FT)　is　crucial　for　the　stable,　efficient　operation　and　pollution　control　of　the　municipal　solid　waste　incineration　(MSWI)　process.　To　address　the　inherent　nonlinearity　and　uncertainty　of　the　incineration　process,　a　FT　control　strategy　is　proposed.　Firstly,　by　analyzing　the　process　characteristics　of　the　MSWI　process　in　terms　of　FT　control,　the　secondary　air　flow　is　selected　as　the　manipulated　variable　to　control　the　FT.　Secondly,　an　FT　prediction　model　based　on　the　Interval　Type-2　Fuzzy　Broad　Learning　System　(IT2FBLS)　is　developed,　incorporating　online　parameter　learning　and　structural　learning　algorithms　to　enhance　prediction　accuracy.　Next,　particle　swarm　rolling　optimization　(PSRO)　is　used　to　solve　the　optimal　control　law　sequence　to　ensure　optimization　efficiency.　Finally,　the　stability　of　the　proposed　method　is　validated　using　Lyapunov　theory,　confirming　the　controller＇s　reliability　in　practical　applications.　Experiments　based　on　actual　operational　data　confirm　the　method＇s　effectiveness.