Adaptive Control of a Flexible Manipulator with Unknown Hysteresis and Intermittent Actuator Faults

In this study, we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults. First, an inverse hysteresis dynamics model is introduced, and then the control input is divided into an expected input and an error compensator. Second, a novel adaptive neural network-based control scheme is proposed to cancel the unknown input hysteresis. Subsequently, by modifying the adaptive laws and local control laws, a fault-tolerant control strategy is applied to address uncertain intermittent actuator faults in a flexible manipulator system. Through the direct Lyapunov theory, the proposed scheme allows the state errors to asymptotically converge to a specified interval. Finally, the effectiveness of the proposed scheme is verified through numerical simulations and experiments.