Time-varying parametric identification of nonlinear structural systems based on STUKF
DU Yongfeng1,2,ZHANG Hao1,ZHAO Lijie1,LI Wanrun1
1.Institute of Earthquake Protection and Disaster Mitigation,Lanzhou University of Technology,Lanzhou 730050,China;
2.Western Center of Disaster Mitigation in Civil Engineering of Ministry of Education,Lanzhou University of Technology,Lanzhou 730050,China
Traditional unscented Kalman filter (UKF) cannot track the changed parameters of nonlinear structural systems.Based on the strong tracking filter principle,a strong tracking unscented Kalman filter (STUKF) method was put forward to identify the time-varying parameters of nonlinear structural systems.Firstly,the fading factor matrix was calculated with output residuals after the measurement update of UKF.Secondly,two fading factor matrices were introduced to adjust the predicted state covariance matrix in real time,the residual sequence was made to be orthogonal and the estimated values of structure parameters were updated rapidly,thus STUKF was made to be capable of tracking the changes of structure parameters.Furthermore,the computational efficiency was improved by taking no sigma points sampling after adjusting the predicted state covariance matrix.Numerical simulation results demonstrated that the proposed method can effecfively identify parameters and changes of nonlinear structural systems,and it has a stronger anti-noise capability.
杜永峰1,2，张浩1，赵丽洁1，李万润1. 基于STUKF的非线性结构系统时变参数识别[J]. 振动与冲击, 2017, 36(7): 171-176.
DU Yongfeng1,2,ZHANG Hao1,ZHAO Lijie1,LI Wanrun1. Time-varying parametric identification of nonlinear structural systems based on STUKF. JOURNAL OF VIBRATION AND SHOCK, 2017, 36(7): 171-176.
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