Abstract: In this study, a method to introduce bicycle wheel longitudinal sliding into the controller is proposed to resolve the balance control issue in unmanned bicycles. First, a linear parameter varying (LPV) dynamic model of the bicycle is introduced. Second, the linear velocity of the bicycle centroid estimated using the Kalman filter algorithm is input into the LPV model as a variable parameter. Finally, using the LPV model with a wheel sliding factor, a reduced-order sliding mode controller is designed to eliminate the influence of wheel longitudinal sliding on the balanced motion of unmanned bicycles. The simulation results demonstrat that the reduced-order sliding mode controller effectively corrected the rolling angle of the bicycle when the longitudinal sliding of the wheel was less than 70%. Additionally, the experimental results of the prototype reveal that the reduced-order sliding mode controller can control the balance movement of the unmanned bicycle on cement ground (approximately 8% longitudinal sliding) and wet grass (approximately 40% longitudinal sliding).