Wastewater　treatment　process　(WWTP)　is　a　complex　industrial　process　with　strong　nonlinear　and　time-varying　dynamic　characteristics.　Dissolved　oxygen　(DO)　concentration　is　a　main　factor　limiting　the　effluent　quality.　Due　to　the　complex　biochemical　reactions,　designing　an　effective　controller　for　this　kind　of　process　is　a　huge　challenge.　To　achieve　efficacious　control　under　actuator　saturation,　a　self-organizing　fuzzy　neural　network　adaptive　tracking　control　method　is　proposed.　Firstly,　a　structured　model　of　actuator　saturation　is　employed　to　ensure　the　prescribed　steady-state　and　transient　tracking　performance.　Secondly,　the　self-organizing　fuzzy　neural　network　is　used　to　identify　the　unknown　dynamics　in　WWTP.　Then,　the　structure　learning　algorithm　with　correlation　entropy　is　used　to　adjust　the　structure　online.　Thirdly,　the　stability　of　the　control　strategy　is　analyzed　and　the　corresponding　stability　conditions　are　given.　Finally,　the　simulation　results　on　benchmark　simulation　model　1　(BSM　1)　verify　the　effectiveness　of　the　control　method.　©　2022　IEEE.