A　scaling　factor　identification　based　self-tuned　feedback　neural　network　fault-tolerant　algorithm　is　proposed　for　space　robot　systems　with　partial　loss　of　actuator　effectiveness.　Firstly,　a　conventional　neural　network　control　algorithm　is　designed　for　the　fault-free　system.　Then,　the　real　scaling　factors　are　identified　by　using　the　scaling　factor　observer.　Finally,　a　self-tuned　feedback　neural　network　fault-tolerant　control　algorithm　is　obtained　by　combining　the　above　neural　network　control　algorithm　with　the　identified　scaling　factors.　The　stability　criteria　of　observers　and　controllers　are　given　strictly　based　on　Lyapunov　function　method.　Numerical　simulation　verifies　the　feasibility　of　the　control　method.　©　2020,　Editorial　Office　of　Control　and　Decision.　All　right　reserved.