Optimization of Fuzzy Control for Magnetorheological Damping Structures
Due to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of a magnetorheological damping structure that adopts semiactive control. Fuzzy control is a relatively appropriate control method, but fuzzy control design is susceptible to human subjective expe...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-01-01
|
| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2017/4341025 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850208205983973376 |
|---|---|
| author | Jianguo Ding Xin Sun Lifeng Zhang Jiaoyan Xie |
| author_facet | Jianguo Ding Xin Sun Lifeng Zhang Jiaoyan Xie |
| author_sort | Jianguo Ding |
| collection | DOAJ |
| description | Due to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of a magnetorheological damping structure that adopts semiactive control. Fuzzy control is a relatively appropriate control method, but fuzzy control design is susceptible to human subjective experience, which will decrease the control effect. This paper proposes new fuzzy control rules based on a genetic algorithm (GA) and particle swarm optimization (PSO) and performs a numerical simulation for a three-layer reinforced concrete frame structure under conditions of an uncontrolled structure, fuzzy control, fuzzy control optimized by GA, fuzzy control optimized by PSO, and GA-optimized FLC control (GA-FLC) proposed by Ali and Ramaswamy (2008). The results show that (1) the fitness values of the convergence of the two types of optimized fuzzy control are close. The speed of the convergence of the fuzzy control optimized by PSO is faster than that of the fuzzy control optimized by GA, but its running speed is slower. (2) Comparing the acceleration and displacement of the structure under the conditions of three different seismic waves, the effect of the optimized fuzzy control is better than that of the human experience fuzzy control and GA-FLC. |
| format | Article |
| id | doaj-art-98b5e0491b6b4dfe98ea94183f52282a |
| institution | OA Journals |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-98b5e0491b6b4dfe98ea94183f52282a2025-08-20T02:10:17ZengWileyShock and Vibration1070-96221875-92032017-01-01201710.1155/2017/43410254341025Optimization of Fuzzy Control for Magnetorheological Damping StructuresJianguo Ding0Xin Sun1Lifeng Zhang2Jiaoyan Xie3School of Science, Nanjing University of Science and Technology, Nanjing, ChinaGuang’an Municipal Bureau of Housing and Urban-Rural Development, Sichuan, ChinaSchool of Science, Nanjing University of Science and Technology, Nanjing, ChinaSchool of Science, Nanjing University of Science and Technology, Nanjing, ChinaDue to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of a magnetorheological damping structure that adopts semiactive control. Fuzzy control is a relatively appropriate control method, but fuzzy control design is susceptible to human subjective experience, which will decrease the control effect. This paper proposes new fuzzy control rules based on a genetic algorithm (GA) and particle swarm optimization (PSO) and performs a numerical simulation for a three-layer reinforced concrete frame structure under conditions of an uncontrolled structure, fuzzy control, fuzzy control optimized by GA, fuzzy control optimized by PSO, and GA-optimized FLC control (GA-FLC) proposed by Ali and Ramaswamy (2008). The results show that (1) the fitness values of the convergence of the two types of optimized fuzzy control are close. The speed of the convergence of the fuzzy control optimized by PSO is faster than that of the fuzzy control optimized by GA, but its running speed is slower. (2) Comparing the acceleration and displacement of the structure under the conditions of three different seismic waves, the effect of the optimized fuzzy control is better than that of the human experience fuzzy control and GA-FLC.http://dx.doi.org/10.1155/2017/4341025 |
| spellingShingle | Jianguo Ding Xin Sun Lifeng Zhang Jiaoyan Xie Optimization of Fuzzy Control for Magnetorheological Damping Structures Shock and Vibration |
| title | Optimization of Fuzzy Control for Magnetorheological Damping Structures |
| title_full | Optimization of Fuzzy Control for Magnetorheological Damping Structures |
| title_fullStr | Optimization of Fuzzy Control for Magnetorheological Damping Structures |
| title_full_unstemmed | Optimization of Fuzzy Control for Magnetorheological Damping Structures |
| title_short | Optimization of Fuzzy Control for Magnetorheological Damping Structures |
| title_sort | optimization of fuzzy control for magnetorheological damping structures |
| url | http://dx.doi.org/10.1155/2017/4341025 |
| work_keys_str_mv | AT jianguoding optimizationoffuzzycontrolformagnetorheologicaldampingstructures AT xinsun optimizationoffuzzycontrolformagnetorheologicaldampingstructures AT lifengzhang optimizationoffuzzycontrolformagnetorheologicaldampingstructures AT jiaoyanxie optimizationoffuzzycontrolformagnetorheologicaldampingstructures |