Title
Predefined performance adaptive control of robotic manipulators with dynamic uncertainties and input saturation constraints
Abstract
In this paper, a novel adaptive control is investigated for robotic manipulators to unify the study of predefined performance control, input saturation and dynamic uncertainties. The focus is to achieve three user-defined performance indices of the closed-loop system with simultaneous existence of input constraints and model uncertainties, that is overshoot, precision within prescribed finite time and predefined steady-state error. To ensure the performance constraints, an error transformation is constructed for the manipulators by two auxiliary functions and embedded into the barrier Lyapunov function (BLF) in the backstepping analysis. Furthermore, the adaptive control strategies and the adaptive anti-saturation compensator are, respectively, developed to address the dynamics uncertainties and the actuator saturation. The Lyapunov analysis is employed to show that all the closed-loop signals are bounded. Finally, simulation studies and experiments on Baxter robot demonstrate the effectiveness of the proposed method.
Year
DOI
Venue
2021
10.1016/j.jfranklin.2021.07.025
Journal of the Franklin Institute
DocType
Volume
Issue
Journal
358
14
ISSN
Citations 
PageRank 
0016-0032
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Weizhi Lyu160.76
Dihua Zhai21407.34
Yuhan Xiong300.34
Yuanqing Xia43132232.57