Carr, S. and Anderson, G. and Grimble, M.J. and Ringwood, John
(1988)
An LQG approach to self-tuning control with application to robotics.
In: IEE International Workshop on Robot Control, April 1988, Oxford.
Abstract
Self-tuning control has been recognised as an effective approach
for mechanical manipulator control design due to its ability to cope
with the presence of nonlinearities and uncertainties in robot dynamic
models. The vast majority of existing self-tuning controllers are based
on a linear plant description, the fact that most industrial processes
are nonlinear is taken into account by regarding the plant as a sequence
of pseudolinear descriptions. Therefore, as the plant operating point
changes, the nonlinear plant dynamics are reflected as time varying
parameters in the linear plant description. The applicability of this
approach has been demonstrated by Koivo and Guo [1] where manipulator
joint angular position is the controlled variable. This work is
extended in Koivo et al [2] to the case in which the manipulator is
controlled directly in the cartesian coordinate system. It is found
that convergence of the parameter estimates may not be achieved during
the finite time over which the· motion takes place. Therefore this
approach is particularly suited to repetitive tasks where the last
estimates from the previous run can be used as the initial estimates. Lelic and Wellstead [3] have successfully applied generalised pole
placement to the control of a 5 axis electrically actuated robot-manipulator.
| Item Type: |
Conference or Workshop Item
(Paper)
|
| Keywords: |
LQG; self-tuning control; robotics; robot-manipulator; |
| Academic Unit: |
Faculty of Science and Engineering > Electronic Engineering |
| Item ID: |
9568 |
| Depositing User: |
Professor John Ringwood
|
| Date Deposited: |
19 Jun 2018 15:19 |
| Refereed: |
Yes |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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