In　order　to　realize　the　human-like　motion　control　of　the　robotic　joint　system　actuated　by　antagonistic　pneumatic　artificial　muscles　(PAMs),　it　is　regarded　as　a　non-linear　optimal　control　problem　with　consideration　of　its　serious　non-linear　properties,　and　the　optimal　performance　indexes　are　determined　according　to　the　minimum　jerk　model　based　on　the　joint　motion　characteristics　of　the　human　arm.　Firstly,　the　robotic　joint　model　is　linearized　with　the　extended　state　observer.　Then,　an　optimal　control　law　is　designed　on　the　linearized　standard　integrator　series　model　to　realize　the　unconstrained　human-like　trajectory　of　the　robotic　joint.　The　simulation　results　show　that　the　proposed　algorithm　can　achieve　human-like　motion　with　a　wide　range　(0　∼　120°),　the　joint　trajectories　are　insensitive　to　load　variation　(1　kg　∼　5　kg),　and　it　demonstrates　good　anti-disturbance　performance　in　joint　motion.　The　proposed　approach　is　validated　through　physical　experiments　on　an　experimental　platform　of　the　robotic　joint,　and　the　design　rules　of　the　tuning　parameters　are　discussed.　Only　two　parameters　are　required　to　be　tuned　in　the　proposed　algorithm.　It　is　suitable　for　human-like　motion　control　of　the　joints　actuated　by　antagonistic　PAMs,　and　can　meet　the　requirements　for　the　intrinsic　safety,　the　motion　compliance　and　the　human-like　motion　patterns　of　collaborative　robots.　©　2019,　Science　Press.　All　right　reserved.