Event-triggered sliding mode control for trajectory tracking of robotic system with signal quantization

This paper deals with robotic systems trajectory tracking problems by designing a new event-triggered sliding mode control (ET-SMC) algorithm with signal quantization. More precisely, an event-triggered control strategy is introduced to the sliding mode control algorithm with robustness to reduce the controller update frequency, so as to reduce the network communication resources consumption and maintain the control accuracy. In addition, the dynamic quantization method is adopted between the controller and the actuator for more communication efficiency. Unlike periodic time-triggered control strategy, a novel event triggering condition which requires no state-dependent variables is discussed for less triggering threshold computations. Furthermore, the minimum interval of adjacent triggering instant based on the new triggering condition can be obtained to avoid the Zeno phenomenon. Finally, simulation results demonstrate the validity of the presented control algorithm and practical experiments with a PHANToM Omni robotic device are given to verify the advanced performances. As a result, the trajectory tracking error is limited within a small range and the control update frequency is evidently reduced.