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Nonlinear systems based on residual filter identification algorithm

Serious deviation from the parameters, while the accuracy of this method is relatively good. Fourth, the proposed method in the earthquake simulation application of the method, based on shaking table test results. Were two structural models of the system identification of nonlinear dynamic response calculation. Simplified test model for the mechanical model shown in Figure l. A wave test input to regulate the response spectrum for the target spectrum of the synthetic seismic waves. And two-way wave input. Than the peak in two directions to take l. 0.8. Test output acceleration response records for the structure calculation using all the identified seismic vibration test schedule, to identify segments were calculated step by step. Linear elastic stage. Volume of the main identified equivalent elastic modulus, damping parameters and the normal stress on the shear stiffness coefficients of a total of six parameters in the nonlinear stage. To maintain the results of linear identification using the same approach to identify the main targets of structural parameters of equivalent strength, shear modulus reduction factor. Nonlinear hysteretic model parameters and other parameters were l2. Calculations show. Described in this paper is the recognition algorithm, the parameter values can be adapted to changing conditions greatly. In the actual calculation process, once a parameter is adjusted in the identification process after the parameters to the real parameters of the volatility near to small. The effective shear modulus, for example, the initial value of the average difference between the calculated and the final 60 or so. But the general process identified by a calculation of the time after. Its value is generally stable. In general the output error method using the system identification method, identification parameters are difficult to stabilize the situation occurred repeatedly jump. Clear that the observation noise. At the same time,[link widoczny dla zalogowanych], using the methods described in this paper, the error function can be rapidly stabilized. As: AI. 1.8 A test model in Figure 2 Figure 2 shows the test model identification in nonlinear phase response and test responses typical calculation results of comparison between the two is a good degree of character sets. Vibration Engineering Section 4 Kango, the conclusion for the general structure of nonlinear seismic response, identification of physical parameters of its structure calculation should take into account colored noise. This change order AR model to simulate the system of colored noise, the development of a class of residual-based filtering system identification algorithm, initially well verified the reliability of this algorithm. System identification based on residual filter algorithm can use other types of optimization algorithms,[link widoczny dla zalogowanych], adapted to the promotion to general nonlinear systems. References [1] Heatt6-Ct, etal-; SystemIdentificationinStructuralDynamics,[link widoczny dla zalogowanych], ASeg feet. , No. 6,1977, pp. 1089 A】】 Od [2] on the history of the text such as: extended Kalman filter touching the wall in the structure parameters of recognition, Identifie. n / ionby] Extande ~ KalmanFilter, ASCg rib. , No12,[link widoczny dla zalogowanych], 1984, pp. 1757--1770 [43 Li Jie; seismic waves in two-way columns with structural mechanics models of multi-storey brick and seismic performance evaluation,[link widoczny dla zalogowanych], PhD thesis, Tongji University. J988 in [5] D-Gro he was: . thm ∞ uJd.. ntfoltbe {f_leersofnoiseandimprove twenty】 eprecisionofid ~ ntieationparametersk | yword ~: nonlineerity.systemidentificati. n.seism.re sin idua】 fllter

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