Task-space bipartite tracking of networked robotic systems via hierarchical finite-time control

• DOI: 10.1007/s11071-020-05675-7
• Publication Date: 2020-05-15T21:02:43Z
• Authors: Yi-De Wu; Ming-Feng Ge; Teng-Fei Ding; Chao-Yang Chen; Guang Ling
• Keywords: 0209 industrial biotechnology; 02 engineering and technology

This paper investigates the finite-time bipartite tracking problem of networked robotic systems (NRSs) with external disturbances in the task space. Based on the sliding mode control theory, a novel hierarchical finite-time control algorithm (HFTCA) is designed to force two antagonistic subgroups of the NRS to reach two arbitrarily small neighborhoods of the leader state with opposite signs in a finite time. The presented HFTCA is composed of the local control layer, which aims to drive the system state to track the estimated state, and the distributed estimator layer, whose objective is to estimate the above-mentioned neighborhoods using other local interactions. By employing the Lyapunov stability theory, we derive some sufficient conditions for guaranteeing the practical convergence of the regulated bipartite tracking errors. Finally, simulation results are presented to demonstrate the effectiveness of the proposed algorithm.