The　on-orbit　operation　of　insertion　and　extraction　of　space　robots　is　a　technology　essential　to　the　assembly　and　maintenance　in　orbit,　satellite　fuel　filling,　failed　satellite　recovery,　especially　modular　in-orbit　assembly　of　micro-spacecraft.　Therefore,　the　force/posture　impedance　control　for　the　on-orbit　operation　of　insertion　and　extraction　is　studied.　Firstly,　the　dynamic　model　of　space　robots＇　system　in　the　form　of　uncontrolled　carrier　position　and　controlled　attitude　is　derived　by　using　the　momentum　conservation　principle.　Through　the　kinematic　constraints　of　the　replacement　component　plug,　the　Jacobi　relationship　of　the　plug　motion　in　the　base　coordinate　system　is　established.　Secondly,　to　achieve　the　output　force　control　of　the　plug　during　the　on-orbit　operation　of　insertion　and　extraction,　a　second-order　linear　impedance　model　is　established　based　on　the　dynamic　relationship　between　the　plug　posture　and　its　output　force　and　the　impedance　control　principle.　Then,　in　order　to　improve　the　stability,　robustness,　and　adaptability　of　the　controller,　an　adaptive　Radial　Basis　Function　Neural　Network　(RBFNN)　is　used　to　approximate　the　uncertainties　in　the　dynamic　model　for　the　force/posture　control　of　the　plug.　Finally,　the　stability　of　the　system　is　verified　by　the　Lyapunov　principle.　The　simulation　results　show　that　the　designed　neural　network　impedance　control　strategy　can　achieve　a　control　accuracy　of　less　than　10(-3)　rad　for　the　plug＇s　attitude　tracking　error,　less　than　10(-3)　m　for　its　position　tracking　error,　and　less　than　0.5　N　for　its　output　force　tracking　error.