Abstract
A stable walking motion requires effective gait balancing and robust posture correction algorithms. However, to develop and implement such intelligent motion algorithms remain a challenging task for researchers. This paper presents an alternative approach in generating a stable Centre-of-Mass (CoM) trajectory by applying augmented model predictive control algorithm to track the robot Zero Moment Point (ZMP). In order to minimize the modeling errors and disturbances, the propose approach is to apply Augmented Model Predictive Control (AMPC) algorithm with on-line time shift and look ahead to process future data to optimize a control signal by minimizing a cost function so that the system is able to track the reference ZMP as close as possible, and at the same time it is able to limit the motion jerk to improve the robot walking stability.
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