In　order　to　solve　the　problems　of　excessive　energy　consumption　and　serious　water　quality　in　wastewater　treatment　process,　a　wastewater　treatment　process　intelligent　optimization　control　method　based　on　knowledge　is　proposed.　Knowledge　model　of　environment　variable　parameters　and　optimal　solutions　are　built　by　memorizing　the　dynamic　processing　information　of　the　multi-objective　intelligent　optimization　algorithm.　The　optimization　algorithm　is　guided　by　the　non-dominated　solution　in　the　knowledge　base,　and　combines　the　oriented　local　area　search　and　the　stochastic　global　search　strategy　to　improve　the　convergence　of　the　algorithm　and　obtains　a　higher　quality　solution.　Finally,　experiment　verification　is　performed　on　the　international　common　simulation　platform　BSM1.　Results　show　that　the　proposed　method　can　reduce　energy　consumption　under　the　premise　of　ensuring　the　quality　of　the　effluent.　Copyright　©　2017　Acta　Automatica　Sinica.　All　rights　reserved.