Human-Simulated Predictive Control of Variable ZMP Trajectory Tracking for Biped Robot

A new human-simulated predictive control scheme for biped robot is presented to solve the problems of variable zero-moment point (ZMP) trajectory tracking. To enhance the adaptability of ZMP based walking control, the expected ZMP can be separated as off-line reference ZMP and variable ZMP, and the preview controller and its inverse system can be used to control the trajectory of the center of mass (CoM). But the single predictive control system have a big tracking error for variable ZMP such as rectangular perturbation, the human-simulated predictive control system overcome these shortcomings because of its strong ability to suppress error. The simulation results verify the effectiveness of the proposed method.