To　achieve　excellent　treatment　performance　of　complex　and　time-varying　characteristics,　the　operation　of　wastewater　treatment　process　(WWTP)　has　been　considered　as　a　dynamic　multiobjective　control　problem.　In　this　paper,　an　optimal　controller,　based　on　a　dynamic　multiobjective　particle　swarm　optimization　(DMOPSO)　algorithm,　is　developed　to　deal　with　the　dynamic　multiple　conflicting　criteria　[i.e.,　effluent　quality　(EQ),　operation　cost,　and　operation　stability].　The　novelties　and　advantages　of　this　proposed　DMOPSO-based　optimal　controller　(DMOPSO-OC)　include　the　following　two　aspects.　First,　an　integrated　optimization　framework,　where　the　multiple　objectives　not　only　conflict　with　each　other　but　also　change　over　time,　is　able　to　catch　more　characteristics　of　WWTP　than　the　existing　works.　Second,　a　DMOPSO　algorithm,　with　an　adaptive　global　best　selection　mechanism,　is　designed　to　solve　the　multiobjective　optimization　problem　(MOP)　for　the　proposed　optimal　controller,　thus　leading　to　a　significant　improvement　of　optimal　synthesis　for　performance.　Finally,　the　proposed　DMOPSO-OC　is　tested　in　the　benchmark　simulation　model　No.　1　(BSM1)　and　implemented　in　a　real　WWTP　to　evaluate　its　effectiveness.　The　experimental　results　demonstrate　that　this　proposed　DMOPSO-OC　can　achieve　a　significant　improvement　in　optimal　control　performance　and　obey　the　requirement　of　multiple　conflicting　criteria.