Adaptive Event-Triggered Practical Tracking Control for a Class of Electrical Flexible-Joint Robotic Manipulators With Input Dead-Zone and Saturation

This paper is devoted to the event-triggered practical tracking control for a class of electrical flexible-joint robot manipulators with input constraints. Remarkably, beside the serious uncertainties reflected from the unknown parameters/matrices and external disturbances, both input dead-zone and saturation are considered while the time derivatives of the reference signal are not necessarily available for feedback. Such three aspects of ingredients lead to the incapability of the traditional control schemes. To solve the control problem, a novel adaptive event-triggered control scheme is proposed in this paper. Specifically, a state transformation is firstly introduced to change the original system into a new one, in which a pivotal dynamic gain is included for the compensation of the uncertainties. Then, for the newly obtained system, an adaptive event-triggered controller is skilfully designed by backstepping method, which two mechanisms are carefully chosen for the updating of one dynamic gain and that of the sampling times of control input, respectively. Finally, it is proven that all the states of the resulting closed-loop system are bounded while the system output practically tracks the reference signal, along with the avoidance of the Zeno phenomenon. A simulation example is provided to demonstrate the efficiency of the proposed theoretical results, while shows the powerful ability of the proposed controller for the compensation of serious system uncertainties and input constraints.