Variable-order stochastic adaptive control of robotic manipulators with a flexible forearm
Resource
Control Applications, 1992., First IEEE Conference on
Journal
First IEEE Conference on Control Applications
Pages
-
Date Issued
1992-09
Date
1992-09
Author(s)
Chu, Yung-Chuan
DOI
N/A
Abstract
An application of a recursive covariance lattice filter to the adaptive estimation and stochastic control of a robotic manipulator with one flexible link is presented. Not only the effective order, but also the corresponding parameters of an autoregression moving average with a bias (ARMAB) prediction model of the manipulator, are updated by a set of pure order-recursive lattice algorithms. The reduced-order prediction model that represents significant dynamics of the plant is used to generate optimal control sequences by minimizing the expectation of a weighted cost functional. In the simulations, the manipulator is modeled by the finite element method and Lagrange's equations. The performance and robustness of the variable-order stochastic adaptive controller are demonstrated by numerical results.>
Type
journal article
File(s)![Thumbnail Image]()
Loading...
Name
00269881.pdf
Size
438.79 KB
Format
Adobe PDF
Checksum
(MD5):97632b13b57097a594c785595926f571