Prescribed-Time Adaptive Fault-Tolerant Formation Control for Multi-Agent Systems Under Actuator Faults and Deception Attacks

This paper develops a distributed adaptive control for second-order nonlinear multi-agent systems that achieves prescribed-time formation tracking under actuator efficiency loss and deception attacks. A smooth time-varying constraint combined with a command-filtered backstepping architecture and radial basis function neural network ensures tracking errors enter a pre-specified neighborhood within a designer-set time$T$, independent of initial conditions. Lyapunov analysis proves boundedness of all closed-loop signals and prescribed-time convergence. Numerical simulations with four agents demonstrate robust tracking under actuator degradation and time-varying deception signals.