Fault-Tolerant Control of Switched Nonlinear Systems Under State Constraints and Multiple Time-Varying Faults

This paper proposes an adaptive fault-tolerant control strategy for nonlinear switched systems subject to state constraints and time-varying faults. Within a backstepping framework, multiple Lyapunov integral barrier functions are constructed to enforce state constraints, while radial basis function neural networks and adaptive laws compensate for actuator and sensor faults. Under average dwell time switching, the closed-loop system is rigorously proven to achieve fast practical finite-time stability and excellent output tracking performance, ensuring all signals remain bounded without violating constraints. The approach is validated via a variable-load nonlinear spring–damper simulation.