Optimal　control　system　plays　an　important　role　in　the　stability　and　safety　of　wastewater　treatment　process　(WWTP).　However,　because　of　the　dynamic　complex　mechanism　of　WWTP,　it　is　challenging　to　decide　the　suitable　set-points　of　manipulated　variables　for　improving　optimal　control　performance　in　the　dynamic　complex　environment.　Therefore,　a　dynamic　multiobjective　optimal　control　with　knowledge-decision　(DMOC-KD)　is　proposed　in　this　paper.　First,　a　dynamic　multiobjective　optimal　control　scheme　is　presented　to　adapt　the　dynamic　complex　environment　of　WWTP.　Second,　an　adaptive　multiobjective　particle　swarm　optimization　(AMOPSO),　based　on　distributed　knowledge,　is　presented　to　determine　the　suitable　optimal　set-points　of　WWTP.　Third,　a　fuzzy　neural　network　(FNN)　control　method　is　designed　to　track　the　obtained　optimal　set-points　for　keeping　effluent　equality　and　reducing　energy　consumption.　Finally,　this　DMOC-KD　is　compared　with　other　optimal　control　strategies　on　benchmark　simulation　model　1　(BSM1).　The　results　show　that　this　DMOC-KD　is　superior　than　most　compared　strategies.　©　2020　IEEE.