| [article] 
					| Titre : | Renovated controller designed by genetic algorithms |  
					| Type de document : | texte imprimé |  
					| Auteurs : | Tzu-Kang Lin, Auteur ; Yi-Lun Chu, Auteur ; Kuo-Chun Chang, Auteur |  
					| Article en page(s) : | pp. 457-475 |  
					| Note générale : | Génie Civil |  
					| Langues : | Anglais (eng) |  
					| Mots-clés : | Genetic algorithms  Smart structural control  Optical fiber sensors |  
					| Index. décimale : | 624.1 Infrastructures.Ouvrages en terre. Fondations. Tunnels |  
					| Résumé : | A novel smart control system based on genetic algorithms (GAs) is proposed in this paper. The system is comprised of three parts: the fiber Bragg grating (FBG) sensor-based sensing network for structural health monitoring, the GA-based location optimizer for sensor arrangement, and the GA-based controller for vibration mitigation under external excitation. To evaluate the performance of the proposed system, an eight-story steel structure was designed specifically to represent a structure with large degrees of freedom. In total 16 FBG sensors were deployed on the structure to implement the concept of a reliable sensing network, and to allow the structure to be monitored precisely under any loading. The advantage of applying a large amount of information from the sensing system is proven theoretically by the GA-based location optimizer. This result greatly supports the recent tendency of distributing sensors around the structure. Two intuitive GA-based controllers are then proposed and demonstrated numerically. It is shown that the structure can be controlled more effectively by the proposed GA-strain controller than by the GA-acceleration controller, which represents the traditional control method. A shaking table test was carried out to examine the entire system. Experimental verification has demonstrated the feasibility of using this system in practice. |  
					| ISSN : | 0098-8847 |  
					| En ligne : | http://www3.interscience.wiley.com/journal/121502317/abstract |  in Earthquake engineering structural dynamics > Vol. 38 N°4  (Avril 2009) . - pp. 457-475
 [article] Renovated controller designed by genetic algorithms [texte imprimé] / Tzu-Kang Lin , Auteur ; Yi-Lun Chu , Auteur ; Kuo-Chun Chang , Auteur . - pp. 457-475. Génie CivilLangues  : Anglais (eng )in Earthquake engineering structural dynamics  > Vol. 38 N°4  (Avril 2009)  . - pp. 457-475 
					| Mots-clés : | Genetic algorithms  Smart structural control  Optical fiber sensors |  
					| Index. décimale : | 624.1 Infrastructures.Ouvrages en terre. Fondations. Tunnels |  
					| Résumé : | A novel smart control system based on genetic algorithms (GAs) is proposed in this paper. The system is comprised of three parts: the fiber Bragg grating (FBG) sensor-based sensing network for structural health monitoring, the GA-based location optimizer for sensor arrangement, and the GA-based controller for vibration mitigation under external excitation. To evaluate the performance of the proposed system, an eight-story steel structure was designed specifically to represent a structure with large degrees of freedom. In total 16 FBG sensors were deployed on the structure to implement the concept of a reliable sensing network, and to allow the structure to be monitored precisely under any loading. The advantage of applying a large amount of information from the sensing system is proven theoretically by the GA-based location optimizer. This result greatly supports the recent tendency of distributing sensors around the structure. Two intuitive GA-based controllers are then proposed and demonstrated numerically. It is shown that the structure can be controlled more effectively by the proposed GA-strain controller than by the GA-acceleration controller, which represents the traditional control method. A shaking table test was carried out to examine the entire system. Experimental verification has demonstrated the feasibility of using this system in practice. |  
					| ISSN : | 0098-8847 |  
					| En ligne : | http://www3.interscience.wiley.com/journal/121502317/abstract | 
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