Intelligent tracking control of a dual-arm wheeled mobile manipulator with dynamic uncertainties
SUMMARYThis paper presents an intelligent control approach that incorporates sliding mode control (SMC) and fuzzy neural network (FNN) into the implementation of back‐stepping control for a path tracking problem of a dual‐arm wheeled mobile manipulator subject to dynamic uncertainties and nonholonom...
Saved in:
Published in | International journal of robust and nonlinear control Vol. 23; no. 8; pp. 839 - 857 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Bognor Regis
Blackwell Publishing Ltd
25.05.2013
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | SUMMARYThis paper presents an intelligent control approach that incorporates sliding mode control (SMC) and fuzzy neural network (FNN) into the implementation of back‐stepping control for a path tracking problem of a dual‐arm wheeled mobile manipulator subject to dynamic uncertainties and nonholonomic constraints. By using the back‐stepping technique, the system equations are reformulated into two levels: the kinematic level and the dynamic level. A sliding manifold is constructed by considering the disturbance free kinematic level equations only. With all the system uncertainties concentrated in the dynamic level, an FNN controller associated with a switching type of control law is employed to enforce sliding mode on the prescribed manifold. All parameter adjustment rules for the proposed controller are derived from the Lyapunov theory such that uniform ultimate boundedness for both the tracking error and the FNN weighting updates is ensured. A simulation study, which compares different control design approaches, is included to illustrate the promise of the proposed SMC–FNN method. Copyright © 2012 John Wiley & Sons, Ltd. |
---|---|
Bibliography: | ark:/67375/WNG-1MZN5L7P-2 ArticleID:RNC2796 istex:208EEA5B26C4C023BB345490F5DEF76805936141 ObjectType-Article-1 SourceType-Scholarly Journals-1 content type line 14 ObjectType-Feature-2 content type line 23 |
ISSN: | 1049-8923 1099-1239 |
DOI: | 10.1002/rnc.2796 |