LAUSR

The event-triggered tracking control is studied for the steer-by-wire (SbW) system with actuator fault, inaccurate dynamic model, and external disturbance. First, an adaptive sliding mode control based on event-triggering mechanism is proposed. The lumped nonlinearity, including friction torque and self-aligning torque of SbW systems, is approximated by an adaptive robust radial basis function neural network (RBFNN). Robust terms of sliding mode control attenuate the negative effects of the actuator fault, modeling error, external disturbance, and event-triggering error on control performance. More importantly, the sliding-mode high-frequency switching control appears in the high-order derivative of sliding variable without increasing the input–output relative degree, thereby eliminating chattering. Furthermore, the designed method can achieve the practical finite-time stability. The proposed event-triggering mechanism can strictly exclude Zeno behavior and economize the communication resources. Finally, simulations and experiments show the effectiveness of the proposed algorithm.