Paper Info
Title
Adaptive Fuzzy Tracking Control of Flexible-Joint Robots With Full-State Constraints
Abstract
This paper reports our study on adaptive fuzzy tracking control for flexible-joint robots with full state constraints. In the control design, fuzzy systems are adopted to identify the totally unknown nonlinear functions and can properly avoid burdensome computations. The tan-type barrier Lyapunov functions are used to deal with state constraints so that even without state constraints, the controller is still valid. By combining the method of backstepping design with adaptive fuzzy control approaches, a novel simpler controller is successfully constructed to ensure that the output tracking errors converge to a sufficiently small neighborhood of the origin, while the constraints on the system states will not be violated during operation. Finally, comparison simulations are presented to demonstrate the effectiveness of the proposed control schemes.
Year
DOI
Venue
2019
10.1109/tsmc.2018.2870642
IEEE Transactions on Systems, Man, and Cybernetics
Keywords
Field
DocType
Robots,Fuzzy systems,Adaptive systems,Backstepping,Nonlinear systems,Control design,Sun
Lyapunov function,Backstepping,Control theory,Nonlinear system,Computer science,Adaptive system,Control theory,Fuzzy logic,Fuzzy control system,Robot
Journal
Volume
Issue
ISSN
49
11
2168-2216
Citations 
PageRank 
References 
8
0.41
0
Authors
4
Name
Order
Citations
PageRank
Wei Sun11298.62
Shun-Feng Su2119497.62
Jian-Wei Xia339838.02
Van-Truong Nguyen4462.20