| Summary: | 碩士 === 國立交通大學 === 土木工程學研究所 === 86 === In this work, an Unsupervised Fuzzy Neural Network(UFN) reasoning model is applied to the domain of structural control based on active control strategy. The UFN reasoning model is based on a single-layer lateral-connected neural network with an unsupervised competing learning algorithm. The basis of the active UFN reasoning structrural control is based on that response of a structure under excitation is governed by a structural dynamic formula, a function of mass, damper, and stiffness of structure. Given a set of instances, consisting of response of structure and corresponding control force, the UFN reasoning model is used to classify these instances into certain clusters. The instances are similar to each other in the same cluster and dissimilar to the instances in other clusters. Herein, two examples of single-degree-of-freedom (SDOF) under earthquake excitations are used to verify the performance of the UFN reasoning model active control model. The results indicate that the proposed control strategy has the capability of reducing the vibration of structures under earthquake excitations.
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