Research Article

Safety-critical nonlinear optimal predictive control with adaptive error elimination algorithm for robotic system

Department of Electrical and Electronic Engineering, Shanghai Institute of Technology, Shanghai, 201418, China

^* Corresponding authors (email: whl7228@126.com)

Received: 30 August 2024
Revised: 8 October 2024
Accepted: 21 October 2024

Abstract

Safety-critical control enables intelligent robots to have better secure operation and resistance to adverse environments, hence greatly enhancing their interaction and adaptability to the environment. In this paper, we propose a safety-critical control scheme for robotic systems using an 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 for the limitation of the template model. In order to be independent of system parameters and disturbances, a sliding mode controller is further designed under an 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 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.