Adaptive control of teleoperation systems with prescribed tracking performance: a BLF-based approach
Yuling Li, Zheng Liu, Zilong Wang, Yixin Yin, Baoyong Zhao
Abstract
Adaptive control for a class of teleoperation systems with prescribed transient-state and steady-state tracking behavior is considered in this paper. Novel sliding variables are proposed such that the performance constraints which characterize the prescribed tracking performance can be addressed by a Barrier Lyapunov Function, and the backstepping-like approaches that are typically employed to the control of robotic systems are avoided. Besides, the acceleration information of the robots which is usually explored in the recently proposed prescribed-performance-based control design, but not easy to be available in real applications, is not included. In this respect, a control scheme of low complexity and straightforward implementation is obtained. The satisfaction of the tracking error convergence is illustrated by theoretical analysis and is verified by comparative simulation studies.