The　traditional　adaptive　filter　and　Filtered-x　LMS　(FxLMS)　algorithm　have　been　widely　used　in　active　noise　control(ANC)　systems.　But　for　the　nonlinearity　in　the　system,　the　linear　control　algorithm　will　be　difficult　to　get　good　control　effect,　while　the　neural　network　can　overcome　the　influences　of　nonlinearity.　In　this　paper,　the　deep　recurrent　neural　network(DRNN)　controller　is　applied　to　ANC　systems　to　improve　noise　cancellation　capability.　Simulation　results　demonstrate　that　the　proposed　DRNN　controller　can　obtain　better　performance　than　the　FxLMS　and　Filtered-x　BP　Neural　Network　(FxBPNN)　in　the　presence　of　strong　nonlinearity.　©　2020　IEEE.