Practical Bipartite Tracking for Networked Robotic Systems via Fixed-Time Estimator-Based Control

Peng Su, Jinqiang Gan, Teng-Fei Ding, Chang-Duo Liang, Ming-Feng Ge and Sergey Dashkovskiy

Complexity, 2021, vol. 2021, 1-15

Abstract: In this paper, the fixed-time practical bipartite tracking problem for the networked robotic systems (NRSs) with parametric uncertainties, input disturbances, and directed signed graphs is investigated. A new fixed-time estimator-based control algorithm for the NRSs is presented to address the abovementioned problem. By applying a sliding surface and the time base generator (TBG) approach, a new stability analysis method is proposed to achieve the fixed-time practical bipartite tracking for the NRSs. We also derive the upper bound of the convergence time for employing the presented control algorithm to solve the practical bipartite tracking problem and further demonstrate that the convergence time is independent of the initial value. Finally, the simulation examples are given to verify the effectiveness of the presented algorithms.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:6593015

DOI: 10.1155/2021/6593015

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