For　the　trajectory　tracking　of　underactuated　autonomous　underwater　vehicle　(AUV)　subject　to　disturbances,　a　disturbance　suppression　and　neural　network　(NN)　compensation　based　control　strategy　is　proposed.　Lyapunov　method　is　used　to　guide　the　overall　design　of　control　system.　To　deal　with　the　underactuation,　Light　of　sight　(LOS)　guidance　is　used　to　establish　the　relationship　between　heading　angle　and　cross-track　error.　To　suppress　the　external　disturbance,　L2-gain　design　is　employed　to　guarantee　the　controller　robustness.　To　improve　the　tracking　accuracy,　on-line　neural　networks　with　guaranteed　stability　are　designed　to　identify　unknown　dynamics　including　the　derivatives　of　virtual　controls　and　errors　induced　by　input　saturation.　Numerical　simulation　is　performed　to　verify　the　effectiveness　of　the　proposed　control　strategy.　Compared　with　sliding　mode　controller　(SMC)　and　disturbance　observer　approaches,　the　proposed　controller　performs　better　in　terms　of　robustness　and　the　input　saturation　is　alleviated.　©　2023　Elsevier　Ltd