Time-Varying Transformation-Based Adaptive Tracking Control of Uncertain Robotic Systems With Event-Triggered Mechanism

In this paper, an adaptive global event-triggered control scheme for uncertain robotic systems, capable of guaranteeing adjustable tracking performance, is developed. Compared with most of the existing results, the proposed control exhibits some features. Firstly, to improve the transient tracking performance without the requirement of large control effort, a time-varying scaling diagonal matrix and an error transformation are constructed so that each element of the tracking error has its own convergence rate, which can be adjusted by selecting the design parameters. Secondly, due to the consideration of decreasing the consumption of network resources, some additional diagonal matrices embedded in the new closed-loop system make the new control gain matrix not symmetric and positive definite, then the stability analysis becomes rather more challenging. To solve this issue, an alternative Lyapunov function is constructed to circumvent the above obstacles. The effectiveness of the proposed approach is verified by a 2-DOF robotic manipulator.