In　order　to　effectively　improve　the　performance　of　wastewater　treatment　denitrification　process,　a　knowledge-data-driven　cooperative　optimal　control　(KDDCOC)　is　proposed.　The　main　work　of　this　paper　includes　the　following　two　points:　First,　a　cooperative　optimal　control　objective　model,　based　on　adaptive　knowledge　kernel　function,　is　designed　to　dynamically　describe　the　cooperative　relationship　among　effluent　quality　(EQ),　pumping　energy　consumption　(PE),　and　key　variables;　Second,　a　knowledge　guide-based　cooperative　optimization　algorithm　(KGCO)　is　proposed　to　quickly　and　accurately　obtain　the　optimal　set-points　of　nitrate　nitrogen　(SNO).　Then,　the　response　speed　of　KDDCOC　is　improved.　A　proportional-integral-derivative　(PID)　controller　is　used　to　track　the　optimal　set-points　of　nitrate　nitrogen.　The　proposed　KDDCOC　is　applied　to　the　benchmark　simulation　model　No.1　(BSM1)　of　wastewater　treatment　process.　The　experimental　results　indicate　that　KDDCOC　can　improve　the　effluent　quality　and　the　efficiency　of　denitrification,　reduce　the　energy　consumption.　©　2024　Science　Press.　All　rights　reserved.