Due　to　the　characteristics　of　strong　coupling　and　high　nonlinearity　in　the　control　process,　an　intelligent　decoupling　control　strategy　based　on　recurrent　fuzzy　neural　network　(RFNN)　is　proposed　in　this　paper　to　control　the　wastewater　treatment　process　(WWTP).　Firstly,　the　architecture　of　the　RFNN　controller　is　designed　with　a　mechanism　analysis　of　WWTP.　Secondly,　a　decoupling　strategy　in　combination　with　a　gradient　descent　search　algorithm　is　used　to　decouple　the　control　loop　of　dissolved　oxygen　(D-O)　concentration　and　nitrate　nitrogen　(S-NO)　concentration.　Finally,　stability　analysis　based　on　a　Lyapunov　function　is　investigated.　The　proposed　approach　has　been　applied　to　the　WWTP　simulation　model.　Compared　to　model　predictive　control,　echo　state　network-based　HDP　(E-HDP),　conventional　RFNN,　and　neural　network　on-line　modelling　and　controlling　methods,　the　proposed　method　has　better　control　performance.