Artificial　intelligence　(AI)　has　found　widespread　application　across　diverse　domains,　including　residential　life　and　product　manufacturing.　Municipal　solid　waste　incineration　(MSWI)　represents　a　significant　avenue　for　realizing　waste-to-energy　(WTE)　objectives,　emphasizing　resource　reuse　and　sustainability.　Theoretically,　AI　holds　the　potential　to　facilitate　optimal　control　of　the　MSWI　process　in　terms　of　achieving　minimal　pollution　emissions　and　maximal　energy　efficiency.　However,　a　noticeable　shortage　exists　in　the　current　research　of　the　review　literature　concerning　AI　in　the　field　of　WTE,　particularly　MSWI,　hindering　a　focused　understanding　of　future　development　directions.　Consequently,　this　study　conducts　an　exhaustive　survey　of　AI　applications　for　optimal　control,　categorizing　them　into　four　fundamental　aspects:　modeling,　control,　optimization,　and　maintenance.　Timeline　diagrams　depicting　the　evolution　of　AI　technologies　in　the　MSWI　process　are　presented　to　offer　an　intuitive　visual　representation.　Each　category　undergoes　meticulous　classification　and　description,　elucidating　the　shortcomings　and　challenges　inherent　in　current　research.　Furthermore,　the　study　articulates　the　future　development　trajectory　of　AI　applications　within　the　four　fundamental　categories,　underscoring　the　contribution　it　makes　to　the　field　of　MSWI　and　WTE.