Adaptive finite-time fault-tolerant control of underactuated mechanical systems with guaranteed transient and steady-state performance.
This paper investigates the finite-time fault-tolerant control problem of underactuated mechanical systems subject to actuator faults, external disturbances, and model uncertainties, with particular emphasis on guaranteed transient and steady-state performance. To address the performance degradation and oscillatory behavior caused by these adverse factors, an adaptive finite-time fault-tolerant control scheme is developed by integrating backstepping design, neural-network approximation, and an error transformation mechanism. A predefined performance function is introduced to characterize both transient and steady-state tracking requirements, including convergence rate, overshoot limitation, and final tracking accuracy. Based on this formulation, a barrier Lyapunov function is constructed to ensure that the tracking errors evolve within prescribed time-varying bounds and converge in practical finite time to a small neighborhood of the origin. In addition, an adaptive upper-bound estimation strategy is incorporated to attenuate the effects of approximation errors and disturbances while improving the smoothness of control inputs. Experimental studies on a laboratory-scale underactuated tower crane show that the proposed method achieves improved transient response, smaller tracking errors, and more effective payload swing suppression than benchmark controllers under actuator fault conditions. These results demonstrate the effectiveness and practical applicability of the proposed scheme for real-time fault-resilient control of underactuated mechanical systems.