This　paper　presents　a　two-level　controller　based　on　neural　network　for　wastewater　treatment　process.　Predictive　optimal　control　scheme　using　neural　network　is　applied　in　the　upper　level　control　unit.　The　optimization　unit　is　designed　to　generate　trajectories　of　oxygen　concentration　and　heterotrophic　concentration.　A　feed-forward　neural　network　is　employed　as　prediction　model.　The　gradient　descent　algorithm　method　is　used　to　realize　the　optimization　procedure.　Local　control　unit　contains　two　PID　controllers　which　maintain　the　dissolved　oxygen　concentration　and　the　heterotrophic　concentration　set-point　trajectories.　Simulation　results　demonstrate　the　effectiveness　of　the　proposed　control　strategy.　©　2010　IEEE.