Aiming　at　the　problem　about　the　movement　balance　of　two-wheeled　self-balancing　mobile　robot,　a　learning　mechanism　of　the　operant　conditioning　theory　based　on　recurrent　neural　network　is　adopted.　The　critical　function　is　approached　and　the　most　superior　choice　to　the　action　is　made　by　recurrent　neural　network.　Thus,　the　two-wheeled　self-balancing　mobile　robot　can　obtain　the　movement　balance　skills　of　controlling　like　a　human　or　animal　by　forming,　developing　and　improving　gradually　in　terms　of　self-organization,　and　solve　the　control　problem　about　the　movement　balance　in　the　free-model　external　environment　through　learning　and　training.　Finally,　a　simulation　experiment　is　designed　and　compared　in　two　states　of　disturbance　and　non-disturbance.　The　simulation　results　show　that　the　Skinner＇s　operation　conditioning　has　a　stronger　ability　of　self-balance　control　and　self-learning,　and　the　robustness　is　good,　and　it　also　has　the　higher　research　significance　in　theory　and　the　application　value　in　project.