Direct discrete-time design for sampled-data Hamiltonian control systems
Direct discrete-time design for sampled-data Hamiltonian control systems
The success in a model-based direct discrete-time design for nonlinear sampled-data control systems depends on the availability of a good discrete-time plant model to use for the design. Unfortunately, even if the continuous-time model of a plant is known, we cannot in general compute the exact discrete-time model of the plant, since it requires computing an explicit analytic solution of a nonlinear differential equation. One way to solve the problem of finding a good model is by using an approximate model of the plant. A general framework for stabilization of sampled-data nonlinear systems via their approximate discrete-time models was presented in [11]. It is suggested that approximate discrete-time models can be obtained using various numerical algorithms, such as Runge-Kutta and multistep methods. Yet, to the best of the authors knowledge, almost all available results on this direction view the systems as dissipative systems, whereas for design purpose, there are many systems that are better modeled as Hamiltonian conservative systems
978-3-540-73889-3
87-98
Laila, Dina Shona
41aa5cf9-3ec2-4fdf-970d-a0a349bfd90c
Astolfi, Alessandro
3045f9a9-e8f3-4f19-9f5d-08364de75cdb
July 2006
Laila, Dina Shona
41aa5cf9-3ec2-4fdf-970d-a0a349bfd90c
Astolfi, Alessandro
3045f9a9-e8f3-4f19-9f5d-08364de75cdb
Laila, Dina Shona and Astolfi, Alessandro
(2006)
Direct discrete-time design for sampled-data Hamiltonian control systems.
Allguwer, F., Fleming, P., Kokotovic, P., Kurzhanski, A.B., Kwakernaak, H., Rantzer, A., Tsitsiklis, J.N., Bullo, Francesco and Fujimoto, Kenji
(eds.)
In Lagrangian and Hamiltonian Methods for Nonlinear Control 2006.
Springer.
.
(doi:10.1007/978-3-540-73890-9_6).
Record type:
Conference or Workshop Item
(Paper)
Abstract
The success in a model-based direct discrete-time design for nonlinear sampled-data control systems depends on the availability of a good discrete-time plant model to use for the design. Unfortunately, even if the continuous-time model of a plant is known, we cannot in general compute the exact discrete-time model of the plant, since it requires computing an explicit analytic solution of a nonlinear differential equation. One way to solve the problem of finding a good model is by using an approximate model of the plant. A general framework for stabilization of sampled-data nonlinear systems via their approximate discrete-time models was presented in [11]. It is suggested that approximate discrete-time models can be obtained using various numerical algorithms, such as Runge-Kutta and multistep methods. Yet, to the best of the authors knowledge, almost all available results on this direction view the systems as dissipative systems, whereas for design purpose, there are many systems that are better modeled as Hamiltonian conservative systems
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10.1007%2F978-3-540-73890-9_6
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Published date: July 2006
Venue - Dates:
3rd IFAC Workshop on Lagrangian and Hamiltonian Methods for Nonlinear Control, Nagoya, Japan, 2006-07-01
Organisations:
Mechatronics
Identifiers
Local EPrints ID: 353761
URI: http://eprints.soton.ac.uk/id/eprint/353761
ISBN: 978-3-540-73889-3
PURE UUID: 1534bfde-0ff9-441a-8325-2ab038688fd4
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Date deposited: 17 Jun 2013 12:48
Last modified: 14 Mar 2024 14:09
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Contributors
Author:
Dina Shona Laila
Author:
Alessandro Astolfi
Editor:
F. Allguwer
Editor:
P. Fleming
Editor:
P. Kokotovic
Editor:
A.B. Kurzhanski
Editor:
H. Kwakernaak
Editor:
A. Rantzer
Editor:
J.N. Tsitsiklis
Editor:
Francesco Bullo
Editor:
Kenji Fujimoto
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