To　reduce　the　ship　roll　motion,　an　adaptive　robust　fin　controller　based　on　a　feedforward　neural　network　is　proposed.　The　dynamics　of　the　fin　actuator　is　considered　in　the　plant　of　a　roll-fin　cascaded　system　with　uncertainties　which　refer　to　as　the　modeling　errors　and　the　environmental　disturbance　induced　by　waves.　An　on-line　feedforward　neural　network　is　constructed　to　account　for　the　uncertainties.　Lyapunov　design　is　employed　to　obtain　the　fin　stabilizer　with　guaranteed　robustness.　Simulation　results　demonstrate　the　validity　of　the　controller　designed　and　the　superior　performance　over　a　conventional　PD　controller.　©　2016　Elsevier　B.V.