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 neurofuzzy 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. ; info:eu-repo/semantics/publishedVersion


    Access

    Download


    Export, share and cite



    Title :

    Optimization of a fuzzy logic controller for MR dampers using ANFIS


    Contributors:

    Publication date :

    2015-01-01


    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629







    AIAA 2001-0316 FUZZY LOGIC MODEL-BASED PREDICTIVE CONTROL OF AIRCRAFT DYNAMICS USING ANFIS

    Nho, K. / Agarwal, R. K. / AIAA | British Library Conference Proceedings | 2001


    Power Optimization of Electric Motor using PID-Fuzzy Logic Controller

    Kholid, Aviseno / Fauzi, Rifky Ahmad / Yunazwin Nazaruddin, Yul et al. | IEEE | 2019