Under the learning automaton frame a bionic self-learning automaton which has autonomous learning mechanism is constructed based on conditioned reflex theory. The bionic self-learning automaton is a 5-tupe and mainly contains: 1) inner set, mainly are perception state set and operant set; 2) oriented core, guide the direction of autonomous learning; 3) learning core, the primitives of learning unit; 4) autonomous learning unit, implement learning computation; 5) operant entropy, measuring the self-organized degree of bionic self-learning automaton. Theory analysis is made for the designed bionic self-learning automaton in the thesis, which theoretically proves the convergence of autonomous learning mechanism in bionic self-learning automaton, namely the operant entropy will converge to minimum with the learning process. And then the designed bionic self-learning automaton which used as the mathematical abstraction and formal tool of robot and used to describe the self-learning behavior of robot is applied to motion control of two-wheeled self-balanced robot. The state sets of bionic self-learning automaton is described by tilt angle and tilt angle rate of robot, and the operant sets is described by control signal of left motor and right motor. Robot doesn’t have t motion balanced skill in initial state, and with the learning proceeding the operant entropy will gradually decrease. After about twenty-five rounds training, the operant entropy gradually tends to minimum. So robot gradually learned the motion balanced skill.