Title
Approximation Based Adaptive Tracking Control Of Uncertain Nonholonomic Mechanical Systems
Keywords
Adaptive control; Neural networks; Nonholonomic mobile robots; Trajectory tracking; Uncertainties
Abstract
In this paper, the trajectory tracking control problem of uncertain nonholonomic mechanical systems is investigated. By separately considering kinematic and dynamic models of a nonholonomic mechanical system, a new adaptive tracking control is proposed based on neural network approximation. The proposed design consists of two steps. First, the nonholonomic kinematic subsystem is transformed into a chained form, and the corresponding optimal control is derived. Second, an adaptive neural control is designed for the dynamic subsystem to make the outputs of the dynamic subsystem (i.e. the inputs to the kinematic subsystem) asymptotically track the optimal control signals chosen for the kinematic subsystem. To show its effectiveness, the proposed control is simulated for a differential-drive wheeled mobile robot.
Publication Date
12-1-2009
Publication Title
Control and Intelligent Systems
Volume
37
Issue
4
Number of Pages
204-211
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.2316/Journal.201.2009.4.201-2048
Copyright Status
Unknown
Socpus ID
77950803226 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/77950803226
STARS Citation
Wang, J.; Qu, Z.; Obeng, M. S.; and Wu, X., "Approximation Based Adaptive Tracking Control Of Uncertain Nonholonomic Mechanical Systems" (2009). Scopus Export 2000s. 11073.
https://stars.library.ucf.edu/scopus2000/11073