How Can Brain Learn to Control a Nonholonomic System?
Humans can often conduct both linear and nonlinear control tasks after a sufficient number of trials, even if they initially do not have sufficient knowledge about the system's dynamics and the way to control it. Theoretically, it is well known that some nonlinear systems cannot be stabilized a...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2010-01-01
|
| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2010/919306 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832549609778446336 |
|---|---|
| author | Noriyasu Homma Shinpei Kato Takakuni Goto Ivo Bukovsky Ryuta Kawashima Makoto Yoshizawa |
| author_facet | Noriyasu Homma Shinpei Kato Takakuni Goto Ivo Bukovsky Ryuta Kawashima Makoto Yoshizawa |
| author_sort | Noriyasu Homma |
| collection | DOAJ |
| description | Humans can often conduct both linear and nonlinear control tasks after a sufficient number of trials, even if they initially do not have sufficient knowledge about the system's dynamics and the way to control it. Theoretically, it is well known that some nonlinear systems cannot be stabilized asymptotically by any linear controllers and we have reported by an f-MRI experiment that different types of information may be involved in linear and nonlinear control tasks, respectively, from a brain function mapping point of view. In this paper, from a controllability analysis, we still show a possibility that human may use a linear control scheme for such nonlinear control tasks by switching the linear controllers with a virtual constraint. It is suggested that the proposed virtual constraint can play an important role to overcome a limitation of the linear controllers and to mimic human control behavior. |
| format | Article |
| id | doaj-art-c30f288a05364508bd65e1544fbba009 |
| institution | Kabale University |
| issn | 1687-9600 1687-9619 |
| language | English |
| publishDate | 2010-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-c30f288a05364508bd65e1544fbba0092025-02-03T06:10:54ZengWileyJournal of Robotics1687-96001687-96192010-01-01201010.1155/2010/919306919306How Can Brain Learn to Control a Nonholonomic System?Noriyasu Homma0Shinpei Kato1Takakuni Goto2Ivo Bukovsky3Ryuta Kawashima4Makoto Yoshizawa5CyberScience Center, Tohoku University, 6-6-05 Aoba, Aramaki, Aoba-ku, Sendai 980-8579, JapanGraduate School of Engineering, Tohoku University, 6-6-05 Aoba, Aramaki, Aoba-ku, Sendai 980-8579, JapanInstitute of Development, Aging and Cancer, Tohoku University, Seiryo-machi 4-1, Aoba-ku, Sendai 980-8575, JapanCyberScience Center, Tohoku University, 6-6-05 Aoba, Aramaki, Aoba-ku, Sendai 980-8579, JapanInstitute of Development, Aging and Cancer, Tohoku University, Seiryo-machi 4-1, Aoba-ku, Sendai 980-8575, JapanCyberScience Center, Tohoku University, 6-6-05 Aoba, Aramaki, Aoba-ku, Sendai 980-8579, JapanHumans can often conduct both linear and nonlinear control tasks after a sufficient number of trials, even if they initially do not have sufficient knowledge about the system's dynamics and the way to control it. Theoretically, it is well known that some nonlinear systems cannot be stabilized asymptotically by any linear controllers and we have reported by an f-MRI experiment that different types of information may be involved in linear and nonlinear control tasks, respectively, from a brain function mapping point of view. In this paper, from a controllability analysis, we still show a possibility that human may use a linear control scheme for such nonlinear control tasks by switching the linear controllers with a virtual constraint. It is suggested that the proposed virtual constraint can play an important role to overcome a limitation of the linear controllers and to mimic human control behavior.http://dx.doi.org/10.1155/2010/919306 |
| spellingShingle | Noriyasu Homma Shinpei Kato Takakuni Goto Ivo Bukovsky Ryuta Kawashima Makoto Yoshizawa How Can Brain Learn to Control a Nonholonomic System? Journal of Robotics |
| title | How Can Brain Learn to Control a Nonholonomic System? |
| title_full | How Can Brain Learn to Control a Nonholonomic System? |
| title_fullStr | How Can Brain Learn to Control a Nonholonomic System? |
| title_full_unstemmed | How Can Brain Learn to Control a Nonholonomic System? |
| title_short | How Can Brain Learn to Control a Nonholonomic System? |
| title_sort | how can brain learn to control a nonholonomic system |
| url | http://dx.doi.org/10.1155/2010/919306 |
| work_keys_str_mv | AT noriyasuhomma howcanbrainlearntocontrolanonholonomicsystem AT shinpeikato howcanbrainlearntocontrolanonholonomicsystem AT takakunigoto howcanbrainlearntocontrolanonholonomicsystem AT ivobukovsky howcanbrainlearntocontrolanonholonomicsystem AT ryutakawashima howcanbrainlearntocontrolanonholonomicsystem AT makotoyoshizawa howcanbrainlearntocontrolanonholonomicsystem |