Discrete-Time Model Reduction of Sampled Systems Using an Enhanced Multiresolutional Dynamic Genetic Algorithm
| dc.contributor | 國立臺灣師範大學電機工程學系 | zh_tw |
| dc.contributor.author | C.-C. Hsu | en_US |
| dc.contributor.author | K.-M. Tse | en_US |
| dc.contributor.author | W.-Y. Wang | en_US |
| dc.date.accessioned | 2014-10-30T09:28:25Z | |
| dc.date.available | 2014-10-30T09:28:25Z | |
| dc.date.issued | 2001-10-10 | zh_TW |
| dc.description.abstract | A framework to automatically generate a reduced-order discrete-time model for the sampled system of a continuous plant preceded by a zero-order hold (ZOH) using an enhanced multi-resolution dynamic genetic algorithm (EMDGA) is proposed in this paper. Chromosomes consisting of the denominator and the numerator parameters of the reduced-order model are coded as a vector with floating-point-type components and searched by the genetic algorithm. Therefore, a stable optimal reduced-order model satisfying the error range specified can be evolutionarily obtained. Because of the use of the multi-resolution dynamic adaptation algorithm and the genetic operators, the convergence rate of the evolution process to search for an optimal reduced-order model can be expedited. Another advantage of this approach is that the reduced discrete-time model evolves based on samples taken directly from the continuous plant, instead of the exact discrete-time model, so that computation time is saved | en_US |
| dc.description.uri | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=969825 | zh_TW |
| dc.identifier | ntnulib_tp_E0604_02_084 | zh_TW |
| dc.identifier.uri | http://rportal.lib.ntnu.edu.tw/handle/20.500.12235/32061 | |
| dc.language | en | zh_TW |
| dc.relation | IEEE International Conference on Systems, Man and Cybernetics, vol. 1,Tucson, AZ, pp. 280-285 | en_US |
| dc.title | Discrete-Time Model Reduction of Sampled Systems Using an Enhanced Multiresolutional Dynamic Genetic Algorithm | en_US |