Aiming　at　addressing　the　problem　that　the　joints　are　easily　destroyed　by　the　impact　torque　during　the　process　of　space　robot　on-orbit　capturing　a　non-cooperative　spacecraft,　a　reinforcement　learning　control　algorithm　combined　with　a　compliant　mechanism　is　proposed　to　achieve　buffer　compliance　control.　The　compliant　mechanism　can　not　only　absorb　the　impact　energy　through　the　deformation　of　its　internal　spring,　but　also　limit　the　impact　torque　to　a　safe　range　by　combining　with　the　compliance　control　strategy.　First　of　all,　the　dynamic　models　of　the　space　robot　and　the　target　spacecraft　before　capture　are　obtained　by　using　the　Lagrange　approach　and　Newton-Euler　method.　After　that,　based　on　the　law　of　conservation　of　momentum,　the　constraints　of　kinematics　and　velocity,　the　integrated　dynamic　model　of　the　post-capture　hybrid　system　is　derived.　Considering　the　unstable　hybrid　system,　a　buffer　compliance　control　based　on　reinforcement　learning　is　proposed　for　the　stable　control.　The　associative　search　network　is　employed　to　approximate　unknown　nonlinear　functions,　an　adaptive　critic　network　is　utilized　to　construct　reinforcement　signal　to　tune　the　associative　search　network.　The　numerical　simulation　shows　that　the　proposed　control　scheme　can　reduce　the　impact　torque　acting　on　joints　by　76.6%　at　the　maximum　and　58.7%　at　the　minimum　in　the　capturing　operation　phase.　And　in　the　stable　control　phase,　the　impact　torque　acting　on　the　joints　were　limited　within　the　safety　threshold,　which　can　avoid　overload　and　damage　of　the　joint　actuators.