Inversion-based adaptive learning control for a one-link flexible manipulator

Author

Wang, Xuezhen ; Chen, Degang

Author_Institution

Dept. of Electr. Eng. & Comput. Eng., Iowa State Univ., Ames, IA, USA

Volume

4

fYear

2002

fDate

6-9 Oct. 2002

Abstract

In this paper, an adaptive learning algorithm Is applied to one-link flexible manipulator. After each repetitive trial, Least-Squares method is used to estimate the system parameters. The output tracking error and the identified system model are used through stable inversion to find the feed forward input, together with the desired state trajectories, for the next trial. An adaptive backstepping based tracking controller is used in each trial to ensure the regulation of the desired state trajectories. Simulation results demonstrate that the proposed learning control scheme is very effective in tip trajectory tracking for a flexible link robotic manipulator.

Keywords

adaptive control; flexible manipulators; learning (artificial intelligence); parameter estimation; position control; adaptive learning; flexible manipulator; identified system; learning control; one-link flexible manipulator; stable inversion; system parameters; tracking error; trajectory tracking; Adaptive control; Control systems; Convergence; Feeds; Manipulator dynamics; Nonlinear dynamical systems; Programmable control; Robots; Sufficient conditions; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 2002 IEEE International Conference on

ISSN

1062-922X

Print_ISBN

0-7803-7437-1

Type

conf

DOI

10.1109/ICSMC.2002.1173365

Filename

1173365