Event-triggered based predefined-time tracking control for robotic manipulators with state and input quantization

This paper addresses the tracking control issue of robotic manipulators using sliding mode control (SMC) methods, emphasizing the requirement of predefined-time convergence for the first time, despite communication resource constraints. Static, event-based dynamic uniform quantizers and a logarithmic quantizer are utilized to ease the communication burden. By leveraging time-varying functions and Lyapunov theory, sufficient gain conditions are derived to ensure that the designed novel predefined-time quantized SMC methods are effective, even though the networked robotic manipulator is subject to external disturbances. Specifically, the tracking error and sliding variable are bounded within a predefined time, while the ability to adjust the convergence bound to a desired level and then have it asymptotically decay to zero is possessed. A series of digital simulations are conducted to substantiate the salient attributes of our approach.