Control Algorithms for Chaotic Systems
This paper presents techniques that actively exploit chaotic behavior to accomplish otherwise-impossible control tasks. The state space is mapped by numerical integration at different system parameter values and trajectory segments from several of these maps are automatically combined into a p...
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| Language: | en_US |
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2004
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| Online Access: | http://hdl.handle.net/1721.1/5985 |
| _version_ | 1826209050205880320 |
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| author | Bradley, Elizabeth |
| author_facet | Bradley, Elizabeth |
| author_sort | Bradley, Elizabeth |
| collection | MIT |
| description | This paper presents techniques that actively exploit chaotic behavior to accomplish otherwise-impossible control tasks. The state space is mapped by numerical integration at different system parameter values and trajectory segments from several of these maps are automatically combined into a path between the desired system states. A fine-grained search and high computational accuracy are required to locate appropriate trajectory segments, piece them together and cause the system to follow this composite path. The sensitivity of a chaotic system's state-space topology to the parameters of its equations and of its trajectories to the initial conditions make this approach rewarding in spite of its computational demands. |
| first_indexed | 2024-09-23T14:16:33Z |
| id | mit-1721.1/5985 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T14:16:33Z |
| publishDate | 2004 |
| record_format | dspace |
| spelling | mit-1721.1/59852019-04-10T17:24:35Z Control Algorithms for Chaotic Systems Bradley, Elizabeth chaos nonlinear dynamics control scientific computation This paper presents techniques that actively exploit chaotic behavior to accomplish otherwise-impossible control tasks. The state space is mapped by numerical integration at different system parameter values and trajectory segments from several of these maps are automatically combined into a path between the desired system states. A fine-grained search and high computational accuracy are required to locate appropriate trajectory segments, piece them together and cause the system to follow this composite path. The sensitivity of a chaotic system's state-space topology to the parameters of its equations and of its trajectories to the initial conditions make this approach rewarding in spite of its computational demands. 2004-10-04T14:25:27Z 2004-10-04T14:25:27Z 1991-03-01 AIM-1278 http://hdl.handle.net/1721.1/5985 en_US AIM-1278 21 p. 3522928 bytes 1357363 bytes application/postscript application/pdf application/postscript application/pdf |
| spellingShingle | chaos nonlinear dynamics control scientific computation Bradley, Elizabeth Control Algorithms for Chaotic Systems |
| title | Control Algorithms for Chaotic Systems |
| title_full | Control Algorithms for Chaotic Systems |
| title_fullStr | Control Algorithms for Chaotic Systems |
| title_full_unstemmed | Control Algorithms for Chaotic Systems |
| title_short | Control Algorithms for Chaotic Systems |
| title_sort | control algorithms for chaotic systems |
| topic | chaos nonlinear dynamics control scientific computation |
| url | http://hdl.handle.net/1721.1/5985 |
| work_keys_str_mv | AT bradleyelizabeth controlalgorithmsforchaoticsystems |