For　the　trajectory　tracking　of　unsymmetric　underactuated　autonomous　underwater　vehicle　(AUV),　a　neural　network　(NN)　and　disturbance　observer-based　strategy　is　proposed.　Disturbance　and　input　saturation　are　considered　in　the　dynamics　of　AUV.　Diffeomorphism　transformation　is　employed　to　obtain　an　equivalent　system　to　the　original　unsymmetric　system.　To　deal　with　the　underactuation,　an　improved　approach　angle　is　proposed　and　an　additional　control　is　designed　to　stabilise　the　velocity　error　in　the　underactuated　sway　motion.　To　deal　with　the　external　disturbance,　an　observer　with　guaranteed　convergence　is　incorporated　into　the　dynamics　controller.　To　deal　with　the　input　constraint,　adaptive　neural　networks　are　designed　to　identify　the　errors　induced　by　input　saturation.　To　avoid　the　calculation　of　time　derivatives　of　virtual　velocities,　command　filters　are　employed.　Numerical　simulation　is　performed　to　verify　the　effectiveness　of　the　proposed　control　strategy.　Under　the　proposed　controller,　both　straight　line　and　curve　trajectories　can　be　tracked　well.　©　2024　Informa　UK　Limited,　trading　as　Taylor　&　Francis　Group.