On numerical differentiation algorithms for nonlinear estimation
Authors: S. Diop, J.W. Grizzle, F. Chaplais, 39th IEEE Conference on Decision and Control, Vol. 2, pp. 1133 - 1138, Dec 2000, Sydney DOI: 10.1109/CDC.2000.912005
Practical methods of differentiating a signal known only through its online samples are much needed, given the numerous areas in control theory and practice where differentiation is encountered. This communication presents theoretical as well as implementation details on several numerical differentiation algorithms which may be useful in the area of nonlinear estimation. In particular, these algorithms may be used as ingredients for alternative solutions to the long-standing problem of observer design for nonlinear systems.
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BibTeX:
@Proceedings{,
author = {S. Diop, J.W. Grizzle, F. Chaplais},
editor = {},
title = {On numerical differentiation algorithms for nonlinear estimation},
booktitle = {39th IEEE Conference on Decision and Control},
volume = {2},
publisher = {},
address = {Sydney},
pages = {1133 - 1138},
year = {2000},
abstract = {Practical methods of differentiating a signal known only through its online samples are much needed, given the numerous areas in control theory and practice where differentiation is encountered. This communication presents theoretical as well as implementation details on several numerical differentiation algorithms which may be useful in the area of nonlinear estimation. In particular, these algorithms may be used as ingredients for alternative solutions to the long-standing problem of observer design for nonlinear systems},
keywords = {Algorithm design and analysis, Automatic control, Control theory, Difference equations, Ear, Estimation error, Inverse problems, Nonlinear systems, Polynomials, Uncertainty}}
Practical methods of differentiating a signal known only through its online samples are much needed, given the numerous areas in control theory and practice where differentiation is encountered. This communication presents theoretical as well as implementation details on several numerical differentiation algorithms which may be useful in the area of nonlinear estimation. In particular, these algorithms may be used as ingredients for alternative solutions to the long-standing problem of observer design for nonlinear systems.
Download PDF - long version
BibTeX:
@Proceedings{,
author = {S. Diop, J.W. Grizzle, F. Chaplais},
editor = {},
title = {On numerical differentiation algorithms for nonlinear estimation},
booktitle = {39th IEEE Conference on Decision and Control},
volume = {2},
publisher = {},
address = {Sydney},
pages = {1133 - 1138},
year = {2000},
abstract = {Practical methods of differentiating a signal known only through its online samples are much needed, given the numerous areas in control theory and practice where differentiation is encountered. This communication presents theoretical as well as implementation details on several numerical differentiation algorithms which may be useful in the area of nonlinear estimation. In particular, these algorithms may be used as ingredients for alternative solutions to the long-standing problem of observer design for nonlinear systems},
keywords = {Algorithm design and analysis, Automatic control, Control theory, Difference equations, Ear, Estimation error, Inverse problems, Nonlinear systems, Polynomials, Uncertainty}}