This　paper　aims　to　address　the　problem　of　the　adaptive　finite-time　neural　control　for　a　class　of　nonlinear　systems　with　the　dynamic　disturbance　and　output　hysteresis.　The　Bouc–Wen　model　is　first　introduced　to　capture　the　output　hysteresis　phenomenon.　The　variable-transformed　method　is　employed　to　resolve　the　problem　that　x1　cannot　be　available　for　measurement　because　of　the　output　hysteresis.　Furthermore,　for　the　sake　of　conquering　the　output　hysteresis　constraint,　the　adaptive　backstepping　control　and　ln-type　barrier　Lyapunov　function　(BLF)　are　combined　in　a　unified　framework,　which　can　guarantee　the　prescribed　constraint　of　the　tracking　error.　In　addition,　the　Nussbaum　function　is　used　to　deal　with　the　unknown　control　gain　problem　(UCGP).　Basing　on　the　new　finite-time　stability　criterion,　an　adaptive　finite　time　controller　is　constructed,　which　can　ensure　that　the　closed-loop　system　is　segi-global　practical　finite-time　stability　(SGPFS).　The　system　states　remain　in　the　defined　compact　sets　and　the　output　constraint　is　not　violated.　Finally,　the　simulation　is　implemented　to　evaluate　the　effectiveness　of　the　proposed　scheme.　©　2021