An　intelligent　controller,　based　on　interval　type-2　fuzzy　neural　networks　(IT2FNN)　was　proposed　for　controlling　dissolved　oxygen　(DO)　concentration　in　municipal　wastewater　treatment　processes.　First,　IT2FNN　was　applied　to　design　a　DO　concentration　controller.　Second,　an　adaptive　learning　algorithm　was　used　to　online　adjust　controller　parameters　such　that　self-adaptability　of　the　IT2FNN-based　DO　controller　could　be　improved.　Finally,　IT2FNN-based　DO　controller　was　tested　in　the　benchmark　simulation　model　no.　2　(BSM2).　The　experimental　results　demonstrate　that　the　controller　is　able　to　accurately　monitor　DO　concentration　in　the　fifth　unit　and　maintain　excellent　control.　©　All　Right　Reserved.