Adaptive Fixed-Time Control of Nonlinear MASs With Actuator Faults

The adaptive fixed-time consensus problem for a class of nonlinear multi-agent systems (MASs) with actuator faults is considered in this paper. To approximate the unknown nonlinear functions in MASs, radial basis function neural networks are used. In addition, the first order sliding mode differentiator is utilized to solve the “explosion of complexity” problem, and a filter error compensation method is proposed to ensure the convergence of filter error in fixed time. With the help of the Nussbaum function, the actuator failure compensation mechanism is constructed. By designing the adaptive fixed-time controller, all signals in MASs are bounded, and the consensus errors between the leader and all followers…

• NN
  National Natural Science Foundation of China

  Award: 62003093,62203119,62033003,62121004
• NS
  Natural Science Foundation of Guangdong Province

  Award: 2022A1515011506