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Dynamic identification of inelastic shear frames by using Prandtl-Ishlinskii model

Farrokh, M ; Sharif University of Technology | 2007

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  1. Type of Document: Article
  2. Publisher: 2007
  3. Abstract:
  4. In this paper, a new method is proposed for the identification of inelastic shear frame structures with hysteresis, using data collected on their dynamic response. It uses the Prandtl-Ishlinskii rate independent model for hysteresis. The proposed identification method is capable of identifying the mass, damping and restoring force of a frame structure, which can be used in forming the equations of motion of the frame. By solving the equations of motion, the dynamic response is predicted. The method is based on the combined using of the Quadratic Programming (QP) and Genetic Algorithms (GA). First, assuming a set of Prandtl-Ishlinskii constants, the QP is used to find the best frame parameters which can be used in its equations of motion to predict its dynamic response with the least error compared to the real data collected on its dynamic response, while the GA is used to find the best Prandtl-Ishlinskii constants for more reduction in the error. To show the capability of the proposed method in this paper, a single degree of freedom (SDOF) frame with bilinear nonlinearity is utilized for identification, and the results show the high capability of the method
  5. Keywords:
  6. Algorithms ; Control nonlinearities ; Control theory ; Data structures ; Diesel engines ; Elasticity ; Equations of motion ; Genetic algorithms ; Hysteresis ; Mechanics ; Open channel flow ; Structural frames ; Dynamic identifications ; Frame structures ; Identification ; Identification methods ; Independent models ; Nonlinearities ; Prandtl-Ishlniskii model ; Real datums ; Restoring forces ; Shear farmes ; Shear frame structures ; Shear frames ; Single degree of freedoms ; Dynamic response
  7. Source: 18th IASTED International Conference on Modelling and Simulation, MOAS 2007, Montreal, QC, 30 May 2007 through 1 June 2007 ; 2007 , Pages 284-288 ; 10218181 (ISSN) ; 9780889866638 (ISBN)
  8. URL: https://dl.acm.org/doi/abs/10.5555/1295645.1295696