Different　patients　have　different　rehabilitation　requirements.　It　is　essential　to　ensure　the　safety　and　comfort　of　patients　at　different　recovery　stages　during　rehabilitation　training.　This　study　proposes　a　multi-mode　adaptive　control　method　to　achieve　a　safe　and　compliant　rehabilitation　training　strategy.　First,　patients＇　motion　intention　and　motor　ability　are　evaluated　based　on　the　average　human-robot　interaction　force　per　task　cycle.　Second,　three　kinds　of　rehabilitation　training　modes-robot-dominant,　patient-dominant,　and　safety-stop-are　established,　and　the　adaptive　controller　can　dexterously　switch　between　the　three　training　modes.　In　the　robot-dominant　mode,　based　on　the　motion　errors,　the　patient＇s　motor　ability,　and　motion　intention,　the　controller　can　adaptively　adjust　its　assistance　level　and　impedance　parameters　to　help　patients　complete　rehabilitation　tasks　and　encourage　them　to　actively　participate.　In　the　patient-dominant　mode,　the　controller　only　adjusts　the　training　speed.　When　the　trajectory　error　is　too　large,　the　controller　switches　to　the　safety-stop　mode　to　ensure　patient　safety.　The　stabilities　of　the　adaptive　controller　under　three　training　modes　are　then　proven　using　Lyapunov　theory.　Finally,　the　effectiveness　of　the　multi-mode　adaptive　controller　is　verified　by　simulation　results.