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Experimental verification of constrained minimum variance unbiased estimator for simultaneous input and state estimation of Bounded Input and Bounded Output (BIBO) type Bouc–Wen hysteretic structural system
Author(s) -
Tamuly Pranjal,
Chakraborty Arunasis,
Das Sandip
Publication year - 2021
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.2648
Subject(s) - bounded function , estimator , robustness (evolution) , control theory (sociology) , minimum variance unbiased estimator , pier , structural system , mathematics , algorithm , mathematical optimization , engineering , structural engineering , computer science , mathematical analysis , statistics , control (management) , artificial intelligence , biochemistry , chemistry , gene
Summary Constraint minimum variance unbiased estimator is improvised for simultaneous input and parameter estimation of the Bouc–Wen hysteretic system of a full‐scale bridge pier. The essential structural properties in this case (i.e., bounded input and bounded output) are incorporated in the form of constraint conditions along with degradation and pinching effects. To demonstrate the efficiency of this algorithm, two different types of sigma points generation schemes (viz., unscented transformed points and cubature quadrature points) are presented here. First, the algorithm is validated using simulated response obtained from a single‐bay single‐storey reinforced concrete frame, whose hysteretic parameters are obtained by minimizing the error between the model and experimentally observed load‐deformation characteristics. The rationale behind the use of experimentally observed hysteresis in simulation is to replicate the actual structure so that the realistic material behaviour is maintained. Once the algorithm is validated, its performance is further demonstrated using experimental results of a full‐scale bridge pier, which is the main objective of this study. The numerical results presented in this paper clearly show the robustness of the proposed algorithm using unscented sigma points, which can identify both hysteretic properties and input excitation with sufficient level of accuracy.