An Improved Predefined-Time Adaptive Neural Control Approach for Nonlinear Multiagent Systems

This paper focuses on the predefined-time adaptive neural tracking control problem for nonlinear multiagent systems (MASs). In contrast to the existing results of the predefined-time control methods, this paper introduces a lemma for achieving predefined-time stability within the framework of backstepping, and the primary distinguishing feature is the ability to predefine the convergence time according to user specifications and the controller design process being influenced by a singular parameter. Meanwhile, a numerical example is presented by using the proposed lemma such that the convergence performance can be ensured by the user practical specification. Moreover, by using the neural networks (NNs) and the…

• NN
  National Natural Science Foundation of China

  Awards: 62103108, 62003052