Distributed Adaptive Fault-Tolerant Control with Prescribed Performance for Nonlinear Multiagent Systems

This paper introduces a distributed adaptive fault-tolerant control scheme for nonlinear multi- agent systems afflicted by actuator failures. The proposed scheme ensures that the consensus- tracking errors of the systems meet the prescribed performance requirements. First, in the backstepping design process, a barrier function is constructed based on the proposed scalar function and normalization function to address the prescribed performance issue. Next, both multi-dimensional Taylor network (MTN) control and robust control techniques are utilized to address unknown nonlinear functions. Continuous switching functions are devised to transition from MTN control to robust control whenever the arguments of the unknown functions surpass the operating range of MTN. This effectively resolves the global problem of the system. Furthermore, a boundary estimation method is proposed to handle actuator failures that may occur infinitely. Stability analysis confirms that all signals in the closed-loop system are globally uniformly ultimately bounded. Additionally, the consensus-tracking errors can always be constrained within prescribed boundaries, achieving global convergence to a prescribed accuracy within a prescribed time. Users can flexibly and independently choose the desired settling time and accuracy, without being restricted by any initial conditions. Simulation results provide evidence of the efficacy of the proposed control method.

Communications in Nonlinear Science and Numerical Simulation