Safety-Critical Nonlinear Optimal Predictive Control with Adaptive Error Elimination \nAlgorithm for Robotic System

\n Safety-critical control enables intelligent robots to have better secure operation and resistance to adverse environment, hence greatly enhance their interaction and adaptability to environment. In this paper, we propose a safety critical control scheme for robotic system using adaptive error elimination algorithm and optimization-based nonlinear optimal predictive control (NOPC) framework. The novelty of the proposed work lies in that an adaptive error elimination controller is designed to deal with the problem of stabilization of walking gait, which ensures that robot joint trajectory can compensate the limitation of template model. In order to be independent of system parameters and disturbances, a sliding mode controller is further designed under uncertain environment. This approach takes into account simultaneously with foot position and orientation based on NOPC optimization. It tracks the modified trajectories constrained with the centroidal momentum dynamics. Finally, simulations is utilized to verify the the effectiveness of the mentioned methods. The results indicate that the tracking effect of joint trajectory is better safety-critical nonlinear optimal predictive control with adaptive error elimination algorithm.\n