A new system identification algorithm, multiple autoregressive exogenous
(ARX) inputs-based Takagi-Sugeno (TS) fuzzy model, is developed to identify nonlinear
behavior of structure-magnetorheological (MR) damper systems. It integrates a set of
ARX models, clustering algorithms, and weighted least squares algorithm with a TS
fuzzy model. Based on a set of input-output data that is generated from building
structures equipped with MR dampers, premise parameters of the ARX-TS fuzzy model
are determined by clustering algorithms. Once the premise part is constructed,
consequent parameters of the ARX-TS fuzzy model are optimized by the weighted least
squares algorithm. To demonstrate the effectiveness of the proposed ARX-TS fuzzy
model, it is applied to a three-, an eight-, a twenty-story building structures. It is
demonstrated from the numerical simulation that the proposed ARX-TS fuzzy algorithm
is effective to identify nonlinear behavior of seismically excited building structures
equipped with MR dampers.
A new semiactive nonlinear fuzzy control (SNFC) algorithm is developed
through integration of multiple Lyapunov-based state feedback gains, a Kalman filter, and a converting algorithm with TS fuzzy interpolation method. First, the nonlinear
ARX-TS fuzzy model is decomposed into a set of linear dynamic models that are
operated in only a local linear operating region. Based on the decomposed models,
multiple Lyapunov-based state feedback controllers are formulated in terms of linear
matrix inequalities (LMIs) such that the structure-MR damper system is globally
asymptotically stable and the performance on transient responses is guaranteed. Then,
the state feedback controllers are integrated with a Kalman filter and a converting
algorithm using a TS fuzzy interpolation method to construct semiactive output feedback
controllers. To demonstrate the effectiveness of the proposed SNFC algorithm, it is
applied to a three-, an eight-, and a twenty-story building structures. It is demonstrated
from the numerical simulation that the proposed SNFC algorithm is effective to control
responses of seismically excited building structures equipped with MR dampers. In
addition, it is shown that the proposed SNFC system is better than a traditional optimal
algorithm, H2/linear quadratic Gaussian-based semiactive control strategy.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2473 |
| Date | 15 May 2009 |
| Creators | Kim, Yeesock |
| Contributors | Hurlebaus, Stefan, Langari, Reza |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | electronic, application/pdf, born digital |
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