Abstract
This paper aims to investigate the fixed-time and predefined-time group-bipartite consensus (FTGBC, PTGBC) problems for uncertain networked Euler-Lagrange systems (NELSs) using neural network (NN). An auxiliary sliding mode variable describing the local communication topology is first introduced within the fixed-time and predefined-time frameworks, and the NN technique is used to estimate online uncertainty of NELSs, which ensures the achievement of the desired FTGBC and PTGBC goals, respectively. Moreover, the allowable upper bound expressions for fixed-time and predefined-time are derived by analyzing the convergence of the closed-loop control systems, thus ensuring the adaptability, stability, and robustness of the proposed FTGBC and PTGBC control schemes, which are further verified by numerical simulation examples.
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