Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/74326
Title: Zeroing neural-dynamics approach and its robust and rapid solution for parallel robot manipulators against superposition of multiple disturbances
Authors: Chen, D
Zhang, Y
Li, S 
Keywords: 70B15
92B20
93B51
External disturbances
Neural network models
Parallel robot manipulators
Real-time kinematic control problem
Robust solution
Zeroing neural-dynamics approach
Issue Date: 2017
Publisher: Elsevier
Source: Neurocomputing, 2017, p. 2 How to cite?
Journal: Neurocomputing 
Abstract: This paper proposes a zeroing neural-dynamics (ZND) approach as well as its associated model for solving the real-time kinematic control problem of parallel robot manipulators. Unlike existing works relying on the plausibly impractical assumption that neural network models are free of external disturbances, the proposed model features the suppression of multiple disturbances in addition to its nonlinear processing and control. Theoretical analyses prove that the ZND approach and its associated model inherently possess robustness. In addition, by using an appropriate activation function, the rapid convergence performance of the corresponding ZND model is further achieved. Simulation studies and comprehensive comparisons substantiate the effectiveness, robustness and superiority of the proposed ZND approach as well as its associated model for solving the real-time kinematic control problem of parallel robot manipulators against the superposition of multiple disturbances. Moreover, results of extensive tests verify that the processing of the ZND model can be accelerated by using an appropriate activation function.
URI: http://hdl.handle.net/10397/74326
ISSN: 0925-2312
EISSN: 1872-8286
DOI: 10.1016/j.neucom.2017.09.032
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

1
Citations as of May 21, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.