Abstract
The main objective of the paper is to present a non-heuristic, mathematically well defined control design to the parallel-type double inverted pendulum. First we apply the recently proposed TP model transformation to generate a finite element convex polytopic representation, namely a Tensor Product model representation (that is equivalent with a kind of TS fuzzy model) of the derived quasi linear parameter varying model of the pendulum system. Then we apply linear matrix inequalities under the parallel distributed compensation control design framework to derive decay rate control with constrain on the control value. Since both steps are executable numerically and automatically one after other, we perform a uniform, tractable and straightforward control design to the pendulum system. In order to validate the resulting controller the paper also presents numerical simulations.
Original language | English |
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Title of host publication | IEEE International Conference on Fuzzy Systems |
Pages | 1374-1380 |
Number of pages | 7 |
DOIs | |
Publication status | Published - 2008 |
Event | 2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008 - Hong Kong, China Duration: Jun 1 2008 → Jun 6 2008 |
Other
Other | 2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008 |
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Country | China |
City | Hong Kong |
Period | 6/1/08 → 6/6/08 |
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ASJC Scopus subject areas
- Software
- Artificial Intelligence
- Applied Mathematics
- Theoretical Computer Science
Cite this
TP model transformation based controller design for the parallel-type double inverted pendulum. / Nagy, Szabolcs; Petres, Zoltán; Baranyi, P.
IEEE International Conference on Fuzzy Systems. 2008. p. 1374-1380 4630551.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - TP model transformation based controller design for the parallel-type double inverted pendulum
AU - Nagy, Szabolcs
AU - Petres, Zoltán
AU - Baranyi, P.
PY - 2008
Y1 - 2008
N2 - The main objective of the paper is to present a non-heuristic, mathematically well defined control design to the parallel-type double inverted pendulum. First we apply the recently proposed TP model transformation to generate a finite element convex polytopic representation, namely a Tensor Product model representation (that is equivalent with a kind of TS fuzzy model) of the derived quasi linear parameter varying model of the pendulum system. Then we apply linear matrix inequalities under the parallel distributed compensation control design framework to derive decay rate control with constrain on the control value. Since both steps are executable numerically and automatically one after other, we perform a uniform, tractable and straightforward control design to the pendulum system. In order to validate the resulting controller the paper also presents numerical simulations.
AB - The main objective of the paper is to present a non-heuristic, mathematically well defined control design to the parallel-type double inverted pendulum. First we apply the recently proposed TP model transformation to generate a finite element convex polytopic representation, namely a Tensor Product model representation (that is equivalent with a kind of TS fuzzy model) of the derived quasi linear parameter varying model of the pendulum system. Then we apply linear matrix inequalities under the parallel distributed compensation control design framework to derive decay rate control with constrain on the control value. Since both steps are executable numerically and automatically one after other, we perform a uniform, tractable and straightforward control design to the pendulum system. In order to validate the resulting controller the paper also presents numerical simulations.
UR - http://www.scopus.com/inward/record.url?scp=55249106172&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=55249106172&partnerID=8YFLogxK
U2 - 10.1109/FUZZY.2008.4630551
DO - 10.1109/FUZZY.2008.4630551
M3 - Conference contribution
AN - SCOPUS:55249106172
SN - 9781424418190
SP - 1374
EP - 1380
BT - IEEE International Conference on Fuzzy Systems
ER -