Multiapproximator-based adaptive fault-tolerant control for teleoperation systems with deferred asymmetric time-varying output constraints

The investigation of the synchronization control problem for a class of nonlinear teleoperation systems with asymmetric time-varying output constraints and actuator failures is critical for the safe implementation of remote control tasks in a complicated environment. This study expands the applicability scope of existing constraint control strategies. The shifting function and the asymmetric barrier Lyapunov function are employed to ensure that the system's output constraints are satisfied regardless of whether the initial values are within the constraint boundary. Thus, the strict assumption related to constraint issues in existing references are effectively removed. Meanwhile, neural learning-based nonlinear disturbance observers are utilized to approximate the lumped uncertainty of teleoperation systems. After that, a multiapproximator-based adaptive fault-tolerant control scheme is proposed to achieve synchronization tracking of teleoperation systems. Compared with other references, the proposed method can guarantee superior control performance, and the outputs of the system never violate the time-varying output boundaries. Finally, simulations and experiments are implemented to verify the feasibility and availability of the proposed control scheme with the teleoperation platform composed of two Phantom Omni 3D Touch robots.