An improved artificial fish swarm algorithm and its application on system identification with a time-delay system
To remedy the low convergence rate and low optimization accuracy of the artificial fish swarm algorithm (AFSA), an improved artificial fish swarm algorithm (IAFSA) was proposed. In the improved algorithm, the artificial fish could adjust the vision and step and form a balance between the local searc...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Science Press
2017-04-01
|
| Series: | 工程科学学报 |
| Subjects: | |
| Online Access: | http://cje.ustb.edu.cn/article/doi/10.13374/j.issn2095-9389.2017.04.018 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850282736641638400 |
|---|---|
| author | CAO Fa-ru FENG Mao-lin |
| author_facet | CAO Fa-ru FENG Mao-lin |
| author_sort | CAO Fa-ru |
| collection | DOAJ |
| description | To remedy the low convergence rate and low optimization accuracy of the artificial fish swarm algorithm (AFSA), an improved artificial fish swarm algorithm (IAFSA) was proposed. In the improved algorithm, the artificial fish could adjust the vision and step and form a balance between the local search and global search by identifying the actual condition. Furthermore, when the artificial fish in the foraging behavior does not find a better position than the current location, it steps forward to the optimal artificial fish by introducing the guide behavior to improved algorithm. The results indicate that the improved algorithm has advantages such as convergence rate, optimization accuracy, and anti local extremum value. The improved algorithm was applied to the system identification with the time-delay model. This algorithm can obtain a precise mathematical model of the controlled object and acquire great identification accuracy in the case of external interference. |
| format | Article |
| id | doaj-art-c61a2f57083a4f63b2d748b06fd26544 |
| institution | OA Journals |
| issn | 2095-9389 |
| language | zho |
| publishDate | 2017-04-01 |
| publisher | Science Press |
| record_format | Article |
| series | 工程科学学报 |
| spelling | doaj-art-c61a2f57083a4f63b2d748b06fd265442025-08-20T01:47:54ZzhoScience Press工程科学学报2095-93892017-04-0139461962510.13374/j.issn2095-9389.2017.04.018An improved artificial fish swarm algorithm and its application on system identification with a time-delay systemCAO Fa-ru0FENG Mao-lin1School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaSchool of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaTo remedy the low convergence rate and low optimization accuracy of the artificial fish swarm algorithm (AFSA), an improved artificial fish swarm algorithm (IAFSA) was proposed. In the improved algorithm, the artificial fish could adjust the vision and step and form a balance between the local search and global search by identifying the actual condition. Furthermore, when the artificial fish in the foraging behavior does not find a better position than the current location, it steps forward to the optimal artificial fish by introducing the guide behavior to improved algorithm. The results indicate that the improved algorithm has advantages such as convergence rate, optimization accuracy, and anti local extremum value. The improved algorithm was applied to the system identification with the time-delay model. This algorithm can obtain a precise mathematical model of the controlled object and acquire great identification accuracy in the case of external interference.http://cje.ustb.edu.cn/article/doi/10.13374/j.issn2095-9389.2017.04.018artificial fish swarm algorithmfunction optimizationsystem identificationtime-delay systems |
| spellingShingle | CAO Fa-ru FENG Mao-lin An improved artificial fish swarm algorithm and its application on system identification with a time-delay system 工程科学学报 artificial fish swarm algorithm function optimization system identification time-delay systems |
| title | An improved artificial fish swarm algorithm and its application on system identification with a time-delay system |
| title_full | An improved artificial fish swarm algorithm and its application on system identification with a time-delay system |
| title_fullStr | An improved artificial fish swarm algorithm and its application on system identification with a time-delay system |
| title_full_unstemmed | An improved artificial fish swarm algorithm and its application on system identification with a time-delay system |
| title_short | An improved artificial fish swarm algorithm and its application on system identification with a time-delay system |
| title_sort | improved artificial fish swarm algorithm and its application on system identification with a time delay system |
| topic | artificial fish swarm algorithm function optimization system identification time-delay systems |
| url | http://cje.ustb.edu.cn/article/doi/10.13374/j.issn2095-9389.2017.04.018 |
| work_keys_str_mv | AT caofaru animprovedartificialfishswarmalgorithmanditsapplicationonsystemidentificationwithatimedelaysystem AT fengmaolin animprovedartificialfishswarmalgorithmanditsapplicationonsystemidentificationwithatimedelaysystem AT caofaru improvedartificialfishswarmalgorithmanditsapplicationonsystemidentificationwithatimedelaysystem AT fengmaolin improvedartificialfishswarmalgorithmanditsapplicationonsystemidentificationwithatimedelaysystem |