With　the　increasing　complexity　and　scale　of　activated　sludge　process　(ASP),　it　is　quite　challenging　to　coordinate　the　performance　indices　with　different　time　scales.　To　address　this　problem,　a　cooperative　optimal　controller　(COC)　is　proposed　to　improve　the　operation　performance　in　this　paper.　First,　a　cooperative　optimal　scheme　is　developed　for　designing　the　control　system,　where　the　different　time-scale　performance　indices　are　formulated　by　two　levels.　Second,　a　data-driven　surrogate-assisted　optimization　(DDSAO)　algorithm　is　provided　to　optimize　the　cooperative　objectives,　where　a　surrogate　model　is　established　for　evaluating　the　feasibility　of　optimal　solutions　based　on　the　minimum　squared　error.　Third,　an　adaptive　predictive　control　strategy　is　investigated　to　derive　the　control　laws　for　improving　the　tracking　control　performance.　Finally,　the　proposed　COC　is　tested　on　benchmark　simulation　model　No.　1　(BSM1).　The　results　demonstrate　that　the　proposed　COC　is　able　to　coordinate　the　multiple　time-scale　performance　indices　and　achieve　the　competitive　optimal　control　performance.