Name
Abstract | ||
|---|---|---|
This paper proposes a multi-input, multi-output (MIMO) nonlinear system identification (SI) of civil structures equipped with magnetorheological (MR) dampers. The nonlinear SI model is developed through the integration of multiple MIMO autoregressive exogenous (ARX) input models, Takagi-Sugeno (TS) fuzzy model, weighted linear least squares, fuzzy C-means and subtractive clustering algorithms. To demonstrate the effectiveness of the MIMO ARX-TS fuzzy model, a seismically excited three-story building equipped with an MR damper is investigated: Parameters of the premise and consequent parts for the proposed model are represented in detail and comparison between the original data and identified one is given. It is shown from the simulation that the proposed nonlinear MIMO ARX-TS fuzzy identification algorithm is effective in estimating nonlinear behavior of a seismically excited building-MR damper system. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.3233/IFS-2011-0482 | Journal of Intelligent and Fuzzy Systems |
Keywords | Field | DocType |
fuzzy model,MIMO fuzzy identification,MIMO ARX-TS fuzzy model,building-MR damper system,nonlinear SI model,multiple MIMO autoregressive exogenous,input model,nonlinear behavior,fuzzy C-means,nonlinear system identification,proposed model,MIMO ARX-TS fuzzy identification | Autoregressive model,Nonlinear system,Control theory,Fuzzy logic,MIMO,Nonlinear system identification,System identification,Linear least squares,Mathematics,Damper | Journal |
Volume | Issue | ISSN |
22 | 4 | 1064-1246 |
Citations | PageRank | References |
5 | 0.54 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yeesock Kim | 1 | 58 | 7.16 |
| Reza Langari | 2 | 150 | 35.75 |
| Stefan Hurlebaus | 3 | 61 | 5.81 |