Adaptive Fault-tolerant Neural Control for Large-scale Systems with Actuator Faults

The active adaptive fault-tolerant neural control problem is discussed for large-scale uncertain systems against actuator faults. The unknown interconnections among subsystems are assumed to be nonlinear, not traditional linear. A general actuator fault model is proposed, which integrates bias and gain time-varying faults. Then, based on Lyapunov stability theory, a novel fault diagnostic algorithm and accommodation scheme are proposed, where the assumptions in the existing works are removed and fault-tolerant controller singularity problem is avoided. Finally, simulation results of near space vehicle show the efficiency of the presented control approach.