To　reduce　the　roll　of　a　surface　ship,　a　robust　fin　controller　based　on　functional-link　neural　networks　is　proposed.　The　plant　consists　of　the　ship　roll　dynamics　and　that　of　the　fin　actuators.　Modeling　errors　and　the　environmental　disturbance　induced　by　waves　are　considered　in　the　cascaded　roll　system,　which　are　identified　by　the　neural　networks.　Lyapunov　function　is　employed　in　the　controller　design,　which　guarantees　the　stability　of　the　fin　stabilizer.　Numerical　simulation　demonstrates　the　good　performance　of　the　roll　reduction　based　on　the　controller　proposed.　©　2013　Springer-Verlag　Berlin　Heidelberg.