Optimization of a Fuzzy Logic Controller for MR dampers using ANFIS

• Type: Summary of Presentation in an International Conference
• Date: 2015

Authors

Manuel T. Braz-César (Author) Other; Rui Carneiro de Barros (Author) FEUP

Conference proceedings International

Title: ICEUBI 2015

Pages: 900-900

ICEUBI 2015, International Conference on Engineering, UBI

Covilhã, Universidade da Beira Interior, , 2 a 4 de Dezembro de 2015

Other information

Abstract (EN): Fuzzy controllers have been successfully applied to a wide range of engineering problems due its robustness and the ability to deal with non-linear plants. Despite the inherent advantages of these controllers, there is no systematic technique for converting human knowledge into the rule base of a fuzzy inference system. Adaptive neuro-fuzzy inference system (ANFIS) is an artificial intelligence technique that has been successfully used for mapping input-output relationships based on available data sets, i.e., to automatically adjust a fuzzy inference system with a backpropagation algorithm based on training data. This paper presents the application of a ANFIS model to optimize the parameters of a fuzzy controller for structural control of a building structure using a MR damper. The results obtained with the neuro-fuzzy controller are compared with those of a passive control modes to assess the performance of the proposed control system in reducing the seismic response of the structure.

Language: English

Type (Professor's evaluation): Scientific