Identification and control of large smart structures Chapter uri icon

abstract

  • In this book, a novel multiple-model approach is proposed in order to model and control nonlinear behavior of large structures equipped with nonlinear smart control devices in a unified framework. First, a novel Nonlinear System Identification (hereinafter as "NSI") algorithm, Multiinput, Multi-output (hereinafter as "MIMO") AutoRegressive eXogenous (hereinafter as "ARX") inputs-based Takagi-Sugeno (hereinafter as "TS") fuzzy model, is developed to identify nonlinear behavior of large structures equipped with smart damper systems. It integrates a set of MIMO 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 large structures equipped with MagnetoRheological (hereinafter as "MR") dampers, premise parameters of the MIMO ARX-TS fuzzy model are determined by the clustering algorithms, while the consequent parameters are optimized by the weighted least squares algorithm. Second, a new Semiactive Nonlinear Fuzzy Control (hereinafter as "SNFC") algorithm is proposed through integration of multiple Lyapunov-based state feedback gains, a Kalman filter, and a converting algorithm with TS fuzzy interpolation method: (1) the nonlinear MIMO ARX-TS fuzzy model is decomposed into a set of linear dynamic models that are operated in only a local linear operating region; (2) Then, based on the decomposed dynamic models, multiple Lyapunov-based state feedback controllers are formulated in terms of linear matrix inequalities (hereinafter as "LMIs") such that the large structure-MR damper system is globally asymptotically stable and the performance on transient responses is also guaranteed; (3) finally, 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 MIMO ARX-TS fuzzy model-based SNFC systems, it is applied to a 3-, an 8-, and a 20-story building structure employing MR dampers. It is demonstrated from the numerical simulations that the proposed MIMO ARXTS fuzzy model-based SNFC algorithm is effective to control responses of seismically excited large building structures equipped with MR dampers. © 2010 Nova Science Publishers, Inc. All rights reserved.

author list (cited authors)

  • Kim, Y., Langari, R., & Hurlebaus, S.

Book Title

  • Engineering Physics and Mechanics: Analyses, Prediction and Applications

publication date

  • January 2011